MLR
Muqtadir Abbas
2024-11-29
##Step 1: Load and Prepare Data
setwd("C:/Users/muqta/Desktop/rdata")
getwd()## [1] "C:/Users/muqta/Desktop/rdata"data=read.csv("karpur.csv")
data## depth caliper ind.deep ind.med gamma phi.N R.deep R.med SP
## 1 5667.0 8.685 618.005 569.781 98.823 0.410 1.618 1.755 -56.587
## 2 5667.5 8.686 497.547 419.494 90.640 0.307 2.010 2.384 -61.916
## 3 5668.0 8.686 384.935 300.155 78.087 0.203 2.598 3.332 -55.861
## 4 5668.5 8.686 278.324 205.224 66.232 0.119 3.593 4.873 -41.860
## 5 5669.0 8.686 183.743 131.155 59.807 0.069 5.442 7.625 -34.934
## 6 5669.5 8.686 109.512 75.633 57.109 0.048 9.131 13.222 -39.769
## 7 5670.0 8.686 63.530 40.841 55.067 0.047 15.741 24.485 -45.882
## 8 5670.5 8.686 40.856 23.879 53.603 0.055 24.476 41.877 -47.122
## 9 5671.0 8.686 32.977 18.041 53.865 0.066 30.324 55.430 -47.035
## 10 5671.5 8.686 32.341 17.374 55.728 0.074 30.921 57.559 -45.988
## 11 5672.0 8.686 34.068 18.540 58.418 0.080 29.353 53.938 -42.025
## 12 5672.5 8.686 34.864 19.586 61.025 0.071 28.683 51.057 -37.950
## 13 5673.0 8.686 33.774 19.550 61.158 0.057 29.608 51.151 -37.165
## 14 5673.5 8.686 31.434 18.600 57.304 0.049 31.812 53.764 -38.205
## 15 5674.0 8.686 28.619 17.732 52.907 0.048 34.942 56.394 -39.222
## 16 5674.5 8.686 25.888 17.915 51.225 0.050 38.627 55.819 -41.094
## 17 5675.0 8.686 23.612 19.009 51.157 0.058 42.350 52.606 -44.447
## 18 5675.5 8.686 21.949 20.089 51.144 0.068 45.561 49.778 -45.718
## 19 5676.0 8.686 21.170 20.776 51.682 0.078 47.237 48.133 -43.077
## 20 5676.5 8.686 21.465 21.336 53.212 0.088 46.588 46.869 -40.023
## 21 5677.0 8.687 22.197 21.797 54.930 0.106 45.051 45.878 -39.362
## 22 5677.5 8.661 22.310 21.913 56.451 0.122 44.823 45.635 -41.019
## 23 5678.0 8.661 21.485 21.631 57.452 0.122 46.544 46.231 -43.708
## 24 5678.5 8.687 20.244 21.136 56.503 0.113 49.398 47.313 -46.170
## 25 5679.0 8.686 19.146 20.665 53.403 0.110 52.229 48.391 -47.884
## 26 5679.5 8.686 18.314 20.324 50.867 0.115 54.603 49.202 -49.715
## 27 5680.0 8.686 17.609 20.081 51.485 0.117 56.790 49.797 -50.814
## 28 5680.5 8.686 17.070 20.014 54.311 0.119 58.583 49.964 -49.884
## 29 5681.0 8.686 16.798 20.296 57.147 0.134 59.529 49.271 -47.826
## 30 5681.5 8.686 16.628 20.830 59.908 0.156 60.141 48.008 -45.931
## 31 5682.0 8.686 16.249 21.188 62.538 0.162 61.541 47.196 -44.556
## 32 5682.5 8.686 15.614 20.937 62.847 0.143 64.045 47.762 -44.570
## 33 5683.0 8.686 14.912 19.943 59.421 0.119 67.059 50.142 -42.812
## 34 5683.5 8.686 14.340 18.611 54.399 0.099 69.738 53.733 -35.723
## 35 5684.0 8.686 13.824 17.523 51.114 0.084 72.339 57.068 -29.950
## 36 5684.5 8.686 13.143 16.796 50.382 0.078 76.089 59.539 -34.705
## 37 5685.0 8.686 12.256 16.157 50.557 0.072 81.594 61.892 -43.658
## 38 5685.5 8.686 11.461 15.688 50.104 0.078 87.250 63.744 -48.317
## 39 5686.0 8.686 11.033 15.656 49.153 0.089 90.640 63.873 -51.604
## 40 5686.5 8.686 11.117 16.126 48.907 0.095 89.952 62.012 -53.147
## 41 5687.0 8.686 11.851 17.157 50.208 0.097 84.378 58.286 -48.450
## 42 5687.5 8.686 13.227 18.814 52.479 0.100 75.602 53.152 -43.635
## 43 5688.0 8.686 14.996 20.884 53.235 0.105 66.685 47.884 -46.345
## 44 5688.5 8.686 16.943 23.124 51.830 0.116 59.020 43.245 -52.680
## 45 5689.0 8.686 18.922 25.513 50.871 0.138 52.849 39.196 -56.057
## 46 5689.5 8.686 20.644 27.752 53.670 0.130 48.440 36.033 -54.393
## 47 5690.0 8.686 21.816 29.075 58.834 0.122 45.838 34.394 -50.262
## 48 5690.5 8.686 22.430 29.069 60.725 0.099 44.584 34.401 -47.173
## 49 5691.0 8.686 22.715 28.267 56.690 0.085 44.025 35.376 -45.518
## 50 5691.5 8.686 22.833 27.396 51.783 0.079 43.797 36.501 -45.045
## 51 5692.0 8.686 22.678 26.676 51.050 0.077 44.096 37.486 -47.185
## 52 5692.5 8.686 22.108 25.995 52.503 0.073 45.232 38.469 -51.319
## 53 5693.0 8.686 21.377 25.442 52.790 0.072 46.779 39.305 -53.534
## 54 5693.5 8.686 20.975 25.363 51.431 0.072 47.676 39.428 -52.998
## 55 5694.0 8.686 21.110 26.007 49.782 0.073 47.370 38.451 -52.467
## 56 5694.5 8.686 21.667 27.214 50.183 0.077 46.153 36.746 -54.153
## 57 5695.0 8.686 22.445 28.501 52.501 0.078 44.554 35.086 -55.533
## 58 5695.5 8.686 23.254 29.419 53.426 0.075 43.002 33.992 -57.248
## 59 5696.0 8.686 24.049 29.875 52.361 0.073 41.582 33.473 -63.093
## 60 5696.5 8.686 24.942 30.237 51.394 0.076 40.092 33.071 -69.001
## 61 5697.0 8.686 25.893 30.883 50.702 0.080 38.620 32.380 -68.758
## 62 5697.5 8.686 26.729 31.739 50.806 0.083 37.413 31.507 -65.268
## 63 5698.0 8.686 27.417 32.554 52.346 0.084 36.473 30.718 -62.689
## 64 5698.5 8.686 28.078 33.323 53.893 0.086 35.615 30.009 -60.658
## 65 5699.0 8.686 28.832 34.135 54.022 0.089 34.684 29.296 -57.222
## 66 5699.5 8.686 29.702 34.970 54.342 0.091 33.668 28.596 -50.392
## 67 5700.0 8.686 30.506 35.732 55.169 0.094 32.781 27.986 -42.585
## 68 5700.5 8.686 31.030 36.242 54.772 0.095 32.227 27.593 -40.939
## 69 5701.0 8.686 31.323 36.351 54.040 0.090 31.926 27.510 -44.804
## 70 5701.5 8.686 31.557 36.190 54.742 0.085 31.689 27.632 -45.252
## 71 5702.0 8.686 31.797 36.030 56.060 0.082 31.450 27.755 -40.075
## 72 5702.5 8.686 31.994 36.070 56.324 0.081 31.256 27.724 -36.857
## 73 5703.0 8.686 32.070 36.307 56.051 0.081 31.182 27.543 -37.840
## 74 5703.5 8.686 32.016 36.599 56.703 0.080 31.234 27.323 -35.935
## 75 5704.0 8.686 31.976 36.767 58.662 0.079 31.274 27.199 -29.613
## 76 5704.5 8.686 32.145 36.868 60.143 0.078 31.109 27.124 -28.016
## 77 5705.0 8.686 32.542 37.128 59.443 0.077 30.730 26.934 -34.092
## 78 5705.5 8.686 33.026 37.580 57.930 0.076 30.280 26.610 -39.142
## 79 5706.0 8.686 33.463 37.990 58.261 0.076 29.884 26.322 -40.381
## 80 5706.5 8.686 33.831 38.246 60.433 0.077 29.559 26.147 -43.333
## 81 5707.0 8.686 34.147 38.463 61.744 0.075 29.285 25.999 -45.303
## 82 5707.5 8.686 34.495 38.705 61.793 0.075 28.990 25.836 -40.991
## 83 5708.0 8.686 34.965 38.937 62.062 0.077 28.600 25.683 -33.291
## 84 5708.5 8.686 35.440 39.286 61.718 0.076 28.217 25.455 -30.364
## 85 5709.0 8.686 35.820 39.772 60.116 0.075 27.917 25.144 -39.109
## 86 5709.5 8.686 36.249 40.286 58.627 0.074 27.587 24.823 -56.700
## 87 5710.0 8.686 36.764 40.708 58.150 0.074 27.200 24.565 -67.331
## 88 5710.5 8.686 37.288 40.657 58.260 0.074 26.818 24.596 -63.344
## 89 5711.0 8.686 37.949 40.528 58.738 0.074 26.351 24.674 -55.999
## 90 5711.5 8.686 38.675 41.404 58.646 0.074 25.857 24.152 -52.760
## 91 5712.0 8.686 39.232 43.043 58.066 0.075 25.489 23.232 -47.765
## 92 5712.5 8.686 39.666 43.698 58.299 0.075 25.210 22.884 -40.611
## 93 5713.0 8.686 40.062 43.256 59.218 0.074 24.961 23.118 -38.684
## 94 5713.5 8.686 40.219 43.068 59.339 0.074 24.864 23.219 -41.997
## 95 5714.0 8.686 40.359 43.498 57.940 0.074 24.778 22.990 -43.989
## 96 5714.5 8.686 40.816 44.060 56.756 0.074 24.500 22.696 -45.149
## 97 5715.0 8.686 41.432 44.538 58.042 0.075 24.136 22.453 -49.723
## 98 5715.5 8.686 42.013 44.819 61.012 0.076 23.802 22.312 -55.055
## 99 5716.0 8.686 42.700 45.000 61.661 0.076 23.419 22.222 -57.676
## 100 5716.5 8.686 43.328 45.336 59.151 0.074 23.080 22.058 -59.311
## 101 5717.0 8.686 43.734 45.809 56.754 0.072 22.866 21.830 -61.040
## 102 5717.5 8.686 44.244 46.527 56.673 0.070 22.602 21.493 -61.936
## 103 5718.0 8.686 45.296 47.920 57.156 0.071 22.077 20.868 -59.396
## 104 5718.5 8.686 47.056 50.292 56.939 0.077 21.251 19.884 -49.869
## 105 5719.0 8.686 49.532 53.772 57.301 0.084 20.189 18.597 -41.314
## 106 5719.5 8.686 52.699 58.396 58.575 0.090 18.976 17.125 -42.559
## 107 5720.0 8.686 56.400 63.962 59.835 0.109 17.731 15.634 -46.634
## 108 5720.5 8.686 60.079 69.647 60.982 0.127 16.645 14.358 -42.119
## 109 5721.0 8.686 63.074 73.890 60.391 0.132 15.854 13.534 -32.452
## 110 5721.5 8.686 65.362 75.623 56.775 0.124 15.299 13.224 -28.139
## 111 5722.0 8.686 67.521 75.890 52.628 0.111 14.810 13.177 -36.138
## 112 5722.5 8.687 70.290 77.116 49.673 0.107 14.227 12.967 -50.320
## 113 5723.0 8.684 74.258 80.806 47.444 0.116 13.467 12.375 -55.865
## 114 5723.5 8.719 79.801 87.255 46.368 0.135 12.531 11.461 -48.214
## 115 5724.0 8.777 87.374 97.286 47.806 0.172 11.445 10.279 -40.924
## 116 5724.5 8.786 97.602 112.551 51.103 0.221 10.246 8.885 -42.323
## 117 5725.0 8.783 111.243 132.762 54.966 0.254 8.989 7.532 -42.817
## 118 5725.5 8.793 127.605 155.780 58.339 0.269 7.837 6.419 -37.306
## 119 5726.0 8.825 145.904 178.486 62.386 0.284 6.854 5.603 -34.103
## 120 5726.5 8.860 166.588 198.342 68.002 0.285 6.003 5.042 -37.465
## 121 5727.0 8.884 190.591 216.753 72.455 0.269 5.247 4.614 -41.251
## 122 5727.5 8.883 215.241 235.779 72.731 0.254 4.646 4.241 -41.149
## 123 5728.0 8.883 235.561 254.282 71.864 0.246 4.245 3.933 -41.055
## 124 5728.5 8.883 249.804 268.000 72.386 0.239 4.003 3.731 -45.210
## 125 5729.0 8.883 261.306 276.318 71.204 0.238 3.827 3.619 -51.431
## 126 5729.5 8.883 272.227 283.673 66.616 0.237 3.673 3.525 -55.275
## 127 5730.0 8.883 284.267 293.998 62.589 0.236 3.518 3.401 -55.515
## 128 5730.5 8.883 297.420 307.293 61.882 0.238 3.362 3.254 -55.220
## 129 5731.0 8.883 310.831 321.639 63.410 0.249 3.217 3.109 -58.226
## 130 5731.5 8.883 324.911 335.983 67.308 0.267 3.078 2.976 -59.881
## 131 5732.0 8.883 340.319 349.812 75.965 0.290 2.938 2.859 -53.130
## 132 5732.5 8.883 355.914 361.868 86.890 0.309 2.810 2.763 -44.281
## 133 5733.0 8.883 369.969 371.446 92.453 0.312 2.703 2.692 -40.799
## 134 5733.5 8.883 381.960 379.591 90.080 0.305 2.618 2.634 -38.356
## 135 5734.0 8.883 392.171 387.277 85.740 0.299 2.550 2.582 -34.213
## 136 5734.5 8.883 400.001 393.623 83.846 0.297 2.500 2.540 -32.116
## 137 5735.0 8.883 403.440 397.043 82.532 0.293 2.479 2.519 -33.681
## 138 5735.5 8.883 401.160 396.602 79.395 0.285 2.493 2.521 -37.748
## 139 5736.0 8.883 394.357 391.839 75.973 0.278 2.536 2.552 -40.692
## 140 5736.5 8.883 384.490 382.050 74.618 0.274 2.601 2.618 -39.624
## 141 5737.0 8.883 371.308 366.978 74.599 0.266 2.693 2.725 -38.126
## 142 5737.5 8.883 355.213 348.936 73.332 0.252 2.815 2.866 -40.571
## 143 5738.0 8.883 339.446 331.516 70.440 0.245 2.946 3.016 -44.372
## 144 5738.5 8.885 327.659 316.684 67.981 0.248 3.052 3.158 -45.528
## 145 5739.0 8.849 320.677 306.903 67.381 0.252 3.118 3.258 -43.376
## 146 5739.5 8.816 316.687 306.366 68.606 0.268 3.158 3.264 -39.945
## 147 5740.0 8.818 314.199 314.881 72.328 0.289 3.183 3.176 -39.327
## 148 5740.5 8.839 313.477 325.550 78.991 0.306 3.190 3.072 -43.036
## 149 5741.0 8.853 315.313 332.915 85.526 0.315 3.171 3.004 -44.870
## 150 5741.5 8.873 320.568 338.620 88.265 0.308 3.119 2.953 -39.932
## 151 5742.0 8.861 329.509 346.153 85.474 0.287 3.035 2.889 -34.493
## 152 5742.5 8.850 338.604 353.192 78.758 0.263 2.953 2.831 -35.171
## 153 5743.0 8.816 341.817 353.069 72.168 0.248 2.925 2.832 -35.805
## 154 5743.5 8.815 337.866 343.293 69.713 0.236 2.960 2.913 -32.597
## 155 5744.0 8.875 331.475 329.172 68.793 0.224 3.017 3.038 -33.546
## 156 5744.5 8.886 327.020 317.872 64.595 0.213 3.058 3.146 -38.000
## 157 5745.0 8.873 325.323 313.193 58.463 0.208 3.074 3.193 -36.057
## 158 5745.5 8.851 324.893 315.407 55.257 0.206 3.078 3.171 -30.256
## 159 5746.0 8.875 324.028 321.987 54.907 0.205 3.086 3.106 -27.925
## 160 5746.5 8.875 322.032 328.099 55.206 0.206 3.105 3.048 -24.263
## 161 5747.0 8.850 319.176 329.419 57.296 0.213 3.133 3.036 -16.129
## 162 5747.5 8.874 315.917 324.825 62.403 0.225 3.165 3.079 -12.025
## 163 5748.0 8.859 312.201 315.995 67.617 0.232 3.203 3.165 -16.155
## 164 5748.5 8.859 306.323 305.021 70.130 0.233 3.264 3.279 -22.223
## 165 5749.0 8.859 295.500 292.834 71.626 0.234 3.384 3.415 -24.688
## 166 5749.5 8.857 278.299 278.818 74.827 0.236 3.593 3.587 -26.678
## 167 5750.0 8.886 257.724 262.061 78.078 0.237 3.880 3.816 -32.128
## 168 5750.5 8.848 240.520 243.229 78.221 0.235 4.158 4.111 -38.667
## 169 5751.0 8.825 229.664 225.498 75.751 0.234 4.354 4.435 -38.102
## 170 5751.5 8.876 223.939 214.037 72.412 0.239 4.465 4.672 -26.988
## 171 5752.0 8.851 223.149 214.544 67.829 0.249 4.481 4.661 -15.035
## 172 5752.5 8.817 230.331 233.060 63.233 0.260 4.342 4.291 -13.871
## 173 5753.0 8.832 247.286 269.126 63.103 0.273 4.044 3.716 -18.139
## 174 5753.5 8.817 272.455 308.937 71.395 0.288 3.670 3.237 -17.824
## 175 5754.0 8.850 298.425 337.072 83.232 0.294 3.351 2.967 -15.786
## 176 5754.5 8.885 322.077 352.056 89.320 0.281 3.105 2.841 -14.781
## 177 5755.0 8.883 342.260 360.649 86.392 0.259 2.922 2.773 -15.595
## 178 5755.5 8.883 354.899 363.721 79.049 0.245 2.818 2.749 -22.367
## 179 5756.0 8.883 355.370 353.396 72.593 0.237 2.814 2.830 -30.197
## 180 5756.5 8.883 346.423 329.824 68.646 0.226 2.887 3.032 -28.350
## 181 5757.0 8.884 333.514 306.944 65.899 0.201 2.998 3.258 -17.945
## 182 5757.5 8.859 320.776 294.268 61.714 0.157 3.117 3.398 -9.171
## 183 5758.0 8.835 312.154 286.462 55.154 0.145 3.204 3.491 -6.289
## 184 5758.5 8.849 310.394 284.101 48.476 0.134 3.222 3.520 -4.059
## 185 5759.0 8.851 311.832 294.349 46.894 0.138 3.207 3.397 4.740
## 186 5759.5 8.873 312.296 312.276 52.937 0.167 3.202 3.202 10.822
## 187 5760.0 8.885 313.466 326.600 61.835 0.201 3.190 3.062 3.608
## 188 5760.5 8.883 319.145 334.740 66.967 0.219 3.133 2.987 -8.134
## 189 5761.0 8.883 330.117 339.604 67.500 0.231 3.029 2.945 -12.672
## 190 5761.5 8.883 344.571 343.313 67.659 0.242 2.902 2.913 -10.676
## 191 5762.0 8.883 358.285 347.426 69.203 0.252 2.791 2.878 -5.540
## 192 5762.5 8.883 366.408 352.059 71.224 0.256 2.729 2.840 0.042
## 193 5763.0 8.883 368.829 355.923 72.471 0.250 2.711 2.810 0.318
## 194 5763.5 8.883 369.223 358.973 71.291 0.252 2.708 2.786 -2.366
## 195 5764.0 8.883 370.323 362.548 66.991 0.248 2.700 2.758 -1.688
## 196 5764.5 8.883 371.311 366.389 64.073 0.227 2.693 2.729 -0.903
## 197 5765.0 8.883 368.798 367.395 65.471 0.224 2.711 2.722 -7.052
## 198 5765.5 8.884 359.365 360.381 68.021 0.224 2.783 2.775 -17.704
## 199 5766.0 8.875 342.225 340.802 68.364 0.212 2.922 2.934 -25.341
## 200 5766.5 8.820 318.438 308.378 66.834 0.176 3.140 3.243 -29.919
## 201 5767.0 8.750 289.441 268.283 64.064 0.122 3.455 3.727 -37.549
## 202 5767.5 8.695 256.083 226.995 58.646 0.079 3.905 4.405 -51.726
## 203 5768.0 8.685 221.943 189.347 50.259 0.067 4.506 5.281 -63.854
## 204 5768.5 8.686 189.053 158.612 41.372 0.055 5.290 6.305 -61.185
## 205 5769.0 8.686 161.401 136.651 34.830 0.044 6.196 7.318 -48.523
## 206 5769.5 8.686 143.207 126.606 31.631 0.050 6.983 7.898 -44.711
## 207 5770.0 8.687 138.423 132.031 32.493 0.072 7.224 7.574 -52.385
## 208 5770.5 8.684 148.518 154.566 37.095 0.108 6.733 6.470 -55.930
## 209 5771.0 8.719 168.994 188.999 43.208 0.150 5.917 5.291 -49.513
## 210 5771.5 8.777 194.183 225.101 50.052 0.188 5.150 4.442 -42.803
## 211 5772.0 8.786 221.230 254.383 57.402 0.211 4.520 3.931 -40.613
## 212 5772.5 8.785 248.679 277.395 62.355 0.224 4.021 3.605 -38.988
## 213 5773.0 8.785 276.610 297.849 63.362 0.230 3.615 3.357 -36.910
## 214 5773.5 8.785 301.159 315.385 61.895 0.231 3.320 3.171 -35.907
## 215 5774.0 8.785 320.139 327.375 59.477 0.231 3.124 3.055 -31.800
## 216 5774.5 8.785 333.208 333.575 56.412 0.232 3.001 2.998 -23.276
## 217 5775.0 8.785 342.515 336.870 54.480 0.232 2.920 2.968 -15.708
## 218 5775.5 8.785 350.397 340.643 54.900 0.233 2.854 2.936 -13.954
## 219 5776.0 8.784 357.528 346.153 56.998 0.236 2.797 2.889 -18.513
## 220 5776.5 8.785 362.676 352.046 60.772 0.242 2.757 2.841 -24.472
## 221 5777.0 8.760 363.616 355.402 67.132 0.250 2.750 2.814 -22.893
## 222 5777.5 8.735 358.871 352.897 74.985 0.258 2.786 2.834 -14.587
## 223 5778.0 8.762 348.729 341.672 81.265 0.259 2.868 2.927 -10.889
## 224 5778.5 8.777 334.168 321.070 83.642 0.261 2.993 3.115 -18.789
## 225 5779.0 8.719 314.375 293.071 81.112 0.256 3.181 3.412 -33.017
## 226 5779.5 8.684 287.599 260.192 74.834 0.240 3.477 3.843 -41.902
## 227 5780.0 8.687 254.779 226.556 67.079 0.211 3.925 4.414 -43.037
## 228 5780.5 8.686 222.486 199.552 60.909 0.177 4.495 5.011 -44.079
## 229 5781.0 8.686 192.743 184.441 59.047 0.153 5.188 5.422 -45.915
## 230 5781.5 8.686 166.700 178.123 61.076 0.149 5.999 5.614 -41.798
## 231 5782.0 8.686 145.501 176.407 63.924 0.164 6.873 5.669 -33.021
## 232 5782.5 8.686 130.927 178.254 66.180 0.184 7.638 5.610 -27.758
## 233 5783.0 8.686 125.022 184.949 69.601 0.203 7.999 5.407 -29.827
## 234 5783.5 8.686 127.965 197.432 75.587 0.217 7.815 5.065 -32.414
## 235 5784.0 8.686 136.911 214.435 81.732 0.228 7.304 4.663 -27.074
## 236 5784.5 8.686 147.390 231.658 83.618 0.234 6.785 4.317 -18.387
## 237 5785.0 8.686 156.278 245.986 82.421 0.240 6.399 4.065 -16.299
## 238 5785.5 8.685 163.185 256.852 82.653 0.247 6.128 3.893 -13.286
## 239 5786.0 8.696 168.968 264.772 83.829 0.252 5.918 3.777 4.024
## 240 5786.5 8.717 173.730 269.785 83.775 0.252 5.756 3.707 20.918
## 241 5787.0 8.705 177.056 271.757 82.622 0.250 5.648 3.680 18.501
## 242 5787.5 8.727 178.795 271.386 82.651 0.249 5.593 3.685 -2.612
## 243 5788.0 8.753 179.055 269.411 84.126 0.249 5.585 3.712 -30.952
## 244 5788.5 8.743 178.416 265.994 85.133 0.252 5.605 3.760 -55.110
## 245 5789.0 8.742 177.874 261.487 83.821 0.256 5.622 3.824 -61.876
## 246 5789.5 8.778 177.880 257.132 81.086 0.258 5.622 3.889 -52.067
## 247 5790.0 8.777 178.239 253.894 79.164 0.260 5.610 3.939 -38.597
## 248 5790.5 8.729 179.273 252.115 79.864 0.262 5.578 3.967 -29.175
## 249 5791.0 8.715 181.612 252.115 82.235 0.264 5.506 3.966 -23.288
## 250 5791.5 8.707 185.436 254.247 82.955 0.264 5.393 3.933 -9.210
## 251 5792.0 8.716 190.602 257.847 82.312 0.261 5.247 3.878 12.932
## 252 5792.5 8.721 196.818 261.736 81.935 0.257 5.081 3.821 25.128
## 253 5793.0 8.710 203.240 265.558 81.282 0.254 4.920 3.766 21.230
## 254 5793.5 8.685 209.091 269.368 80.878 0.255 4.783 3.712 13.967
## 255 5794.0 8.711 214.291 272.370 81.457 0.256 4.667 3.671 6.974
## 256 5794.5 8.737 218.770 273.731 81.920 0.259 4.571 3.653 -1.268
## 257 5795.0 8.710 222.113 273.980 81.608 0.263 4.502 3.650 -2.078
## 258 5795.5 8.708 224.257 274.316 80.977 0.266 4.459 3.645 1.060
## 259 5796.0 8.745 225.409 275.087 80.617 0.267 4.436 3.635 -4.967
## 260 5796.5 8.752 225.601 275.801 82.194 0.272 4.433 3.626 -19.473
## 261 5797.0 8.754 225.101 276.158 84.679 0.285 4.442 3.621 -29.025
## 262 5797.5 8.719 224.406 276.352 85.890 0.288 4.456 3.619 -27.821
## 263 5798.0 8.708 223.737 276.450 85.673 0.290 4.470 3.617 -24.421
## 264 5798.5 8.719 223.118 276.249 85.159 0.286 4.482 3.620 -33.321
## 265 5799.0 8.752 222.630 275.694 84.904 0.287 4.492 3.627 -51.631
## 266 5799.5 8.764 222.263 275.063 85.332 0.289 4.499 3.635 -59.327
## 267 5800.0 8.749 221.978 274.728 85.130 0.288 4.505 3.640 -55.784
## 268 5800.5 8.753 221.842 274.896 84.213 0.285 4.508 3.638 -57.366
## 269 5801.0 8.774 222.030 275.630 83.500 0.281 4.504 3.628 -61.023
## 270 5801.5 8.789 222.801 277.130 82.856 0.276 4.488 3.608 -49.171
## 271 5802.0 8.750 224.491 279.530 82.385 0.272 4.455 3.577 -29.236
## 272 5802.5 8.727 226.997 282.137 83.209 0.267 4.405 3.544 -25.205
## 273 5803.0 8.777 229.296 283.795 83.911 0.264 4.361 3.524 -32.334
## 274 5803.5 8.753 229.672 283.705 82.670 0.262 4.354 3.525 -27.528
## 275 5804.0 8.694 226.613 280.564 81.612 0.262 4.413 3.564 -16.881
## 276 5804.5 8.686 219.292 271.220 81.902 0.263 4.560 3.687 -17.035
## 277 5805.0 8.678 207.496 252.840 81.630 0.260 4.819 3.955 -16.411
## 278 5805.5 8.621 191.406 227.040 79.018 0.243 5.225 4.405 -4.650
## 279 5806.0 8.586 172.015 198.881 74.402 0.211 5.813 5.028 1.223
## 280 5806.5 8.588 151.181 172.559 67.680 0.177 6.615 5.795 -9.986
## 281 5807.0 8.588 129.700 147.135 60.430 0.167 7.710 6.797 -30.158
## 282 5807.5 8.588 106.726 122.255 55.445 0.158 9.370 8.180 -47.861
## 283 5808.0 8.588 83.963 99.440 53.330 0.151 11.910 10.056 -48.123
## 284 5808.5 8.588 64.030 81.046 51.726 0.142 15.618 12.339 -32.592
## 285 5809.0 8.588 48.912 66.573 49.024 0.129 20.445 15.021 -23.411
## 286 5809.5 8.588 39.573 55.973 45.149 0.115 25.270 17.866 -29.845
## 287 5810.0 8.588 36.148 50.027 40.558 0.100 27.664 19.989 -40.416
## 288 5810.5 8.588 35.923 47.789 36.092 0.085 27.838 20.925 -48.316
## 289 5811.0 8.588 35.281 46.025 32.883 0.071 28.344 21.727 -52.295
## 290 5811.5 8.588 33.112 42.589 31.523 0.059 30.201 23.480 -53.726
## 291 5812.0 8.588 30.654 37.786 31.117 0.050 32.622 26.465 -55.663
## 292 5812.5 8.588 28.766 32.904 30.446 0.043 34.763 30.391 -56.247
## 293 5813.0 8.588 27.375 28.731 29.703 0.037 36.529 34.806 -52.338
## 294 5813.5 8.588 26.425 25.469 29.152 0.031 37.843 39.264 -44.176
## 295 5814.0 8.588 25.646 22.969 27.810 0.026 38.992 43.537 -35.849
## 296 5814.5 8.588 24.486 20.855 26.103 0.021 40.839 47.951 -32.413
## 297 5815.0 8.588 22.917 18.962 25.828 0.017 43.635 52.736 -31.343
## 298 5815.5 8.588 21.407 17.498 27.802 0.015 46.713 57.148 -27.433
## 299 5816.0 8.588 20.095 16.530 30.636 0.015 49.765 60.497 -22.656
## 300 5816.5 8.587 18.910 15.915 32.983 0.016 52.882 62.834 -22.967
## 301 5817.0 8.588 18.007 15.742 34.204 0.019 55.535 63.525 -29.707
## 302 5817.5 8.564 17.443 16.108 34.833 0.022 57.331 62.083 -36.633
## 303 5818.0 8.538 17.064 16.691 36.249 0.034 58.601 59.913 -32.184
## 304 5818.5 8.564 16.938 17.193 38.675 0.056 59.038 58.164 -14.288
## 305 5819.0 8.563 17.277 17.898 41.279 0.088 57.881 55.872 3.177
## 306 5819.5 8.563 18.021 19.160 44.154 0.136 55.491 52.193 6.512
## 307 5820.0 8.589 18.777 20.677 48.234 0.193 53.256 48.362 -2.257
## 308 5820.5 8.587 19.158 21.860 52.297 0.238 52.197 45.745 -13.485
## 309 5821.0 8.588 19.239 22.440 53.231 0.258 51.979 44.563 -25.262
## 310 5821.5 8.588 19.210 22.303 49.368 0.265 52.055 44.836 -37.982
## 311 5822.0 8.588 18.845 21.197 42.646 0.258 53.064 47.178 -47.068
## 312 5822.5 8.587 17.743 19.204 35.890 0.246 56.362 52.072 -50.614
## 313 5823.0 8.589 16.037 16.968 30.687 0.237 62.357 58.935 -50.035
## 314 5823.5 8.563 14.196 15.144 27.919 0.223 70.445 66.031 -45.280
## 315 5824.0 8.563 12.526 13.868 27.042 0.209 79.837 72.106 -40.774
## 316 5824.5 8.589 11.127 12.950 26.273 0.202 89.870 77.219 -45.208
## 317 5825.0 8.587 10.092 12.233 25.243 0.199 99.091 81.744 -52.780
## 318 5825.5 8.588 9.455 11.696 25.012 0.198 105.760 85.501 -50.856
## 319 5826.0 8.588 9.039 11.307 25.425 0.198 110.627 88.440 -41.124
## 320 5826.5 8.588 8.695 10.985 25.463 0.195 115.006 91.035 -38.940
## 321 5827.0 8.588 8.425 10.695 24.896 0.191 118.698 93.501 -50.852
## 322 5827.5 8.588 8.245 10.440 24.234 0.189 121.284 95.782 -67.040
## 323 5828.0 8.588 8.127 10.167 23.474 0.189 123.050 98.353 -73.950
## 324 5828.5 8.588 8.032 9.941 22.676 0.191 124.498 100.589 -71.495
## 325 5829.0 8.588 7.969 9.998 22.149 0.194 125.486 100.017 -69.495
## 326 5829.5 8.588 7.955 10.292 22.766 0.194 125.702 97.168 -66.201
## 327 5830.0 8.588 7.967 10.436 24.034 0.192 125.523 95.825 -54.542
## 328 5830.5 8.588 7.964 10.284 25.001 0.190 125.562 97.235 -44.783
## 329 5831.0 8.588 7.936 10.123 25.394 0.188 126.008 98.782 -47.977
## 330 5831.5 8.588 7.931 10.112 25.831 0.187 126.084 98.896 -52.414
## 331 5832.0 8.588 8.013 10.107 26.434 0.185 124.799 98.943 -45.110
## 332 5832.5 8.588 8.163 10.070 27.196 0.183 122.497 99.304 -35.242
## 333 5833.0 8.588 8.349 10.159 28.068 0.184 119.779 98.436 -32.892
## 334 5833.5 8.588 8.727 10.504 28.516 0.193 114.586 95.202 -32.565
## 335 5834.0 8.588 9.416 11.238 27.980 0.204 106.201 88.984 -26.871
## 336 5834.5 8.588 10.104 12.353 26.782 0.207 98.973 80.954 -19.615
## 337 5835.0 8.588 10.568 13.269 26.462 0.207 94.622 75.362 -18.143
## 338 5835.5 8.588 11.061 13.565 27.462 0.215 90.411 73.721 -23.974
## 339 5836.0 8.588 11.855 13.727 28.794 0.221 84.353 72.851 -35.205
## 340 5836.5 8.588 12.939 14.472 29.132 0.217 77.286 69.100 -48.249
## 341 5837.0 8.588 14.262 15.954 28.212 0.211 70.114 62.681 -56.359
## 342 5837.5 8.588 15.465 17.927 28.343 0.207 64.661 55.783 -56.850
## 343 5838.0 8.588 15.948 19.670 33.199 0.206 62.705 50.839 -52.475
## 344 5838.5 8.588 15.837 20.285 42.932 0.209 63.142 49.298 -46.477
## 345 5839.0 8.588 15.960 19.982 53.224 0.215 62.657 50.046 -46.257
## 346 5839.5 8.588 16.720 19.882 59.646 0.222 59.808 50.297 -54.566
## 347 5840.0 8.588 17.781 20.336 60.212 0.226 56.238 49.173 -61.195
## 348 5840.5 8.588 18.655 20.952 57.709 0.225 53.604 47.728 -56.993
## 349 5841.0 8.588 19.139 21.717 54.547 0.224 52.249 46.048 -45.867
## 350 5841.5 8.588 19.390 22.760 51.116 0.226 51.573 43.937 -34.957
## 351 5842.0 8.588 19.674 24.013 48.594 0.225 50.829 41.644 -25.349
## 352 5842.5 8.588 20.215 25.817 46.929 0.212 49.468 38.734 -18.233
## 353 5843.0 8.588 21.712 29.432 43.158 0.200 46.056 33.977 -14.730
## 354 5843.5 8.588 25.363 36.735 38.381 0.192 39.427 27.222 -13.262
## 355 5844.0 8.588 31.889 48.497 37.670 0.193 31.358 20.620 -15.333
## 356 5844.5 8.588 41.842 64.301 42.085 0.209 23.899 15.552 -25.532
## 357 5845.0 8.588 56.653 84.463 49.931 0.235 17.652 11.840 -33.477
## 358 5845.5 8.588 75.205 108.906 59.370 0.262 13.297 9.182 -25.103
## 359 5846.0 8.588 93.814 134.149 68.383 0.286 10.659 7.454 -16.237
## 360 5846.5 8.588 108.762 153.295 75.429 0.295 9.194 6.523 -23.111
## 361 5847.0 8.588 119.808 162.135 79.962 0.304 8.347 6.168 -31.431
## 362 5847.5 8.588 131.022 164.460 78.902 0.310 7.632 6.081 -27.972
## 363 5848.0 8.588 145.621 170.211 70.933 0.304 6.867 5.875 -22.820
## 364 5848.5 8.588 162.165 184.661 62.105 0.288 6.167 5.415 -21.430
## 365 5849.0 8.588 178.543 204.671 60.664 0.274 5.601 4.886 -15.891
## 366 5849.5 8.588 195.652 227.480 65.942 0.268 5.111 4.396 -4.573
## 367 5850.0 8.588 216.658 252.066 71.218 0.266 4.616 3.967 -0.281
## 368 5850.5 8.588 242.925 277.219 73.074 0.264 4.116 3.607 -10.418
## 369 5851.0 8.588 274.372 301.788 73.254 0.261 3.645 3.314 -20.713
## 370 5851.5 8.588 306.271 325.096 73.396 0.253 3.265 3.076 -19.745
## 371 5852.0 8.588 333.446 343.655 72.650 0.243 2.999 2.910 -16.142
## 372 5852.5 8.588 349.971 351.706 70.084 0.235 2.857 2.843 -17.070
## 373 5853.0 8.588 349.177 343.359 66.647 0.226 2.864 2.912 -17.390
## 374 5853.5 8.588 327.543 315.062 62.838 0.222 3.053 3.174 -17.401
## 375 5854.0 8.588 290.072 270.645 57.347 0.221 3.447 3.695 -19.838
## 376 5854.5 8.588 247.545 219.582 50.170 0.222 4.040 4.554 -19.474
## 377 5855.0 8.588 208.981 170.669 43.110 0.225 4.785 5.859 -10.625
## 378 5855.5 8.588 169.996 127.866 37.631 0.228 5.883 7.821 3.656
## 379 5856.0 8.588 129.701 93.059 35.090 0.232 7.710 10.746 11.737
## 380 5856.5 8.588 92.702 66.739 35.113 0.238 10.787 14.984 2.136
## 381 5857.0 8.588 65.856 48.242 35.333 0.241 15.185 20.729 -18.440
## 382 5857.5 8.588 49.541 37.005 34.479 0.244 20.185 27.024 -31.007
## 383 5858.0 8.588 41.407 30.538 33.339 0.245 24.150 32.746 -33.234
## 384 5858.5 8.588 38.413 26.746 33.282 0.240 26.033 37.388 -35.160
## 385 5859.0 8.588 37.664 25.233 34.645 0.239 26.551 39.631 -34.471
## 386 5859.5 8.588 37.354 25.023 37.034 0.243 26.771 39.963 -28.905
## 387 5860.0 8.588 36.792 24.946 39.376 0.245 27.180 40.087 -28.497
## 388 5860.5 8.588 35.974 24.759 41.180 0.249 27.798 40.390 -36.150
## 389 5861.0 8.588 35.136 24.639 42.354 0.253 28.461 40.586 -39.541
## 390 5861.5 8.588 34.520 24.701 43.473 0.255 28.969 40.484 -36.232
## 391 5862.0 8.588 34.498 24.921 44.493 0.254 28.987 40.126 -36.102
## 392 5862.5 8.588 35.439 25.176 44.288 0.252 28.218 39.721 -35.006
## 393 5863.0 8.588 37.125 25.347 42.617 0.251 26.936 39.453 -24.792
## 394 5863.5 8.588 38.779 25.502 41.534 0.250 25.787 39.213 -14.225
## 395 5864.0 8.588 39.933 25.771 42.324 0.252 25.042 38.803 -17.738
## 396 5864.5 8.588 40.748 26.139 43.256 0.257 24.541 38.256 -29.345
## 397 5865.0 8.588 41.356 26.601 41.476 0.264 24.180 37.592 -30.518
## 398 5865.5 8.588 41.909 27.203 37.175 0.266 23.861 36.761 -18.245
## 399 5866.0 8.588 42.793 28.031 33.152 0.263 23.368 35.674 -9.312
## 400 5866.5 8.588 44.226 29.198 31.944 0.261 22.611 34.249 -13.582
## 401 5867.0 8.588 46.015 30.707 33.204 0.260 21.732 32.566 -22.105
## 402 5867.5 8.588 47.753 32.308 34.499 0.259 20.941 30.952 -22.359
## 403 5868.0 8.588 49.059 33.864 34.398 0.254 20.383 29.530 -13.959
## 404 5868.5 8.588 49.826 35.523 34.055 0.246 20.070 28.151 -12.012
## 405 5869.0 8.588 50.449 37.499 34.131 0.243 19.822 26.667 -24.988
## 406 5869.5 8.588 51.679 39.935 34.700 0.245 19.350 25.041 -37.784
## 407 5870.0 8.588 54.406 43.398 35.993 0.246 18.380 23.042 -34.971
## 408 5870.5 8.588 58.920 49.000 37.361 0.243 16.972 20.408 -22.106
## 409 5871.0 8.588 64.706 57.105 38.337 0.236 15.455 17.512 -11.450
## 410 5871.5 8.588 71.987 67.058 40.475 0.233 13.892 14.913 -6.276
## 411 5872.0 8.588 81.095 78.844 43.732 0.232 12.331 12.683 -4.506
## 412 5872.5 8.588 89.537 92.638 46.016 0.229 11.169 10.795 -6.644
## 413 5873.0 8.588 94.215 105.805 47.495 0.224 10.614 9.451 -12.643
## 414 5873.5 8.588 96.460 114.889 47.863 0.220 10.367 8.704 -18.061
## 415 5874.0 8.588 100.433 121.371 46.164 0.214 9.957 8.239 -16.998
## 416 5874.5 8.588 109.811 131.574 43.541 0.210 9.107 7.600 -9.858
## 417 5875.0 8.588 127.644 150.928 43.290 0.211 7.834 6.626 -6.619
## 418 5875.5 8.588 154.922 180.288 46.853 0.208 6.455 5.547 -15.288
## 419 5876.0 8.588 187.921 217.112 55.135 0.208 5.321 4.606 -24.533
## 420 5876.5 8.588 221.420 257.074 66.740 0.212 4.516 3.890 -19.293
## 421 5877.0 8.588 254.314 295.764 78.295 0.221 3.932 3.381 -9.786
## 422 5877.5 8.588 287.305 330.706 85.483 0.233 3.481 3.024 -12.019
## 423 5878.0 8.588 317.538 361.138 86.535 0.237 3.149 2.769 -23.554
## 424 5878.5 8.588 347.923 387.751 84.415 0.238 2.874 2.579 -32.804
## 425 5879.0 8.588 379.542 411.987 83.591 0.248 2.635 2.427 -32.978
## 426 5879.5 8.588 407.723 433.903 84.797 0.255 2.453 2.305 -27.289
## 427 5880.0 8.588 429.465 452.565 88.371 0.261 2.329 2.210 -27.761
## 428 5880.5 8.588 447.193 468.000 94.450 0.273 2.236 2.137 -34.665
## 429 5881.0 8.588 463.536 480.680 98.801 0.288 2.157 2.080 -34.719
## 430 5881.5 8.588 476.470 491.737 100.389 0.300 2.099 2.034 -28.507
## 431 5882.0 8.588 485.796 501.992 102.304 0.308 2.059 1.992 -28.957
## 432 5882.5 8.588 492.960 510.840 104.160 0.313 2.029 1.958 -36.701
## 433 5883.0 8.588 498.941 517.523 102.373 0.317 2.004 1.932 -40.276
## 434 5883.5 8.588 504.378 523.301 98.344 0.319 1.983 1.911 -35.806
## 435 5884.0 8.588 510.435 530.527 96.969 0.319 1.959 1.885 -30.020
## 436 5884.5 8.588 517.992 540.253 99.315 0.319 1.931 1.851 -28.864
## 437 5885.0 8.588 526.231 552.576 101.789 0.325 1.900 1.810 -33.402
## 438 5885.5 8.588 533.826 565.711 102.294 0.334 1.873 1.768 -40.061
## 439 5886.0 8.588 541.051 577.757 102.432 0.338 1.848 1.731 -40.362
## 440 5886.5 8.588 548.548 587.378 103.271 0.338 1.823 1.702 -33.289
## 441 5887.0 8.588 556.528 594.887 104.091 0.352 1.797 1.681 -32.717
## 442 5887.5 8.588 565.220 601.691 105.144 0.381 1.769 1.662 -40.938
## 443 5888.0 8.588 573.543 608.438 106.272 0.395 1.743 1.644 -39.144
## 444 5888.5 8.588 578.303 612.861 106.907 0.395 1.729 1.632 -27.744
## 445 5889.0 8.588 577.119 610.891 108.067 0.401 1.733 1.637 -29.811
## 446 5889.5 8.588 572.159 602.302 109.935 0.402 1.748 1.660 -41.723
## 447 5890.0 8.587 568.674 592.701 110.756 0.403 1.758 1.687 -40.388
## 448 5890.5 8.590 567.360 587.049 110.501 0.402 1.763 1.703 -29.728
## 449 5891.0 8.555 562.515 583.427 111.210 0.395 1.778 1.714 -26.547
## 450 5891.5 8.498 550.984 576.528 111.676 0.384 1.815 1.735 -31.723
## 451 5892.0 8.488 535.251 564.342 111.365 0.371 1.868 1.772 -37.954
## 452 5892.5 8.490 517.409 548.500 112.286 0.357 1.933 1.823 -42.839
## 453 5893.0 8.490 497.254 531.159 112.397 0.340 2.011 1.883 -44.366
## 454 5893.5 8.490 473.381 511.920 107.713 0.328 2.112 1.953 -41.188
## 455 5894.0 8.490 444.421 489.246 100.488 0.319 2.250 2.044 -33.131
## 456 5894.5 8.490 414.425 464.611 95.062 0.309 2.413 2.152 -23.712
## 457 5895.0 8.490 386.934 439.596 89.907 0.295 2.584 2.275 -17.555
## 458 5895.5 8.490 361.826 411.586 82.374 0.282 2.764 2.430 -18.152
## 459 5896.0 8.490 332.784 378.802 73.221 0.279 3.005 2.640 -25.413
## 460 5897.0 8.490 256.084 292.891 58.146 0.279 3.905 3.414 -34.640
## 461 5897.5 8.490 217.849 239.164 53.848 0.281 4.590 4.181 -32.349
## 462 5898.0 8.490 181.175 190.005 52.426 0.280 5.519 5.263 -26.569
## 463 5898.5 8.490 145.639 152.401 53.798 0.282 6.866 6.562 -24.443
## 464 5899.0 8.490 110.132 119.997 55.173 0.287 9.080 8.333 -38.254
## 465 5899.5 8.490 78.453 89.547 54.247 0.290 12.747 11.167 -57.541
## 466 5900.0 8.490 56.671 65.198 52.414 0.289 17.646 15.338 -55.923
## 467 5900.5 8.490 45.589 49.352 51.057 0.286 21.935 20.262 -36.912
## 468 5901.0 8.490 39.611 39.857 49.126 0.283 25.246 25.090 -27.936
## 469 5901.5 8.490 35.226 33.418 46.298 0.278 28.388 29.924 -30.482
## 470 5902.0 8.490 31.780 28.739 42.799 0.269 31.466 34.797 -32.117
## 471 5902.5 8.490 29.079 25.428 39.180 0.260 34.389 39.326 -37.693
## 472 5903.0 8.490 27.107 23.268 36.473 0.253 36.891 42.977 -37.470
## 473 5903.5 8.490 25.800 21.963 34.839 0.250 38.760 45.531 -15.592
## 474 5904.0 8.490 24.798 21.066 33.340 0.247 40.326 47.470 3.778
## 475 5904.5 8.490 23.747 20.322 32.160 0.243 42.111 49.207 -7.033
## 476 5905.0 8.490 22.597 19.714 31.853 0.240 44.254 50.726 -29.528
## 477 5905.5 8.490 21.642 19.089 32.235 0.241 46.207 52.386 -36.685
## 478 5906.5 8.490 21.207 17.472 31.960 0.243 47.155 57.235 -32.716
## 479 5907.0 8.490 20.799 16.760 31.389 0.246 48.080 59.668 -33.135
## 480 5907.5 8.490 19.903 16.175 32.410 0.254 50.245 61.822 -33.501
## 481 5908.0 8.490 18.890 15.595 34.627 0.263 52.939 64.121 -31.056
## 482 5908.5 8.488 17.913 15.018 36.770 0.267 55.827 66.588 -10.740
## 483 5909.0 8.500 16.968 14.580 39.313 0.268 58.933 68.587 13.993
## 484 5909.5 8.522 16.052 14.278 42.426 0.266 62.299 70.037 12.456
## 485 5910.0 8.498 15.168 13.963 43.946 0.264 65.926 71.619 -9.897
## 486 5910.5 8.498 14.318 13.593 43.849 0.264 69.842 73.566 -23.451
## 487 5911.0 8.522 13.522 13.243 43.890 0.264 73.956 75.510 -23.510
## 488 5911.5 8.500 12.810 12.960 44.599 0.264 78.063 77.162 -11.738
## 489 5912.0 8.488 12.191 12.753 44.200 0.265 82.028 78.413 3.525
## 490 5912.5 8.490 11.651 12.573 43.033 0.264 85.832 79.535 4.490
## 491 5913.0 8.490 11.180 12.386 42.880 0.264 89.445 80.738 -6.342
## 492 5913.5 8.490 10.757 12.189 43.639 0.259 92.962 82.043 -12.468
## 493 5914.0 8.490 10.325 12.001 43.533 0.262 96.852 83.323 -15.181
## 494 5914.5 8.490 9.874 11.803 43.279 0.262 101.279 84.726 -22.706
## 495 5915.0 8.490 9.448 11.522 43.820 0.263 105.842 86.791 -31.993
## 496 5915.5 8.490 9.073 11.156 44.002 0.262 110.224 89.641 -43.904
## 497 5916.0 8.490 8.740 10.836 42.589 0.257 114.420 92.287 -54.716
## 498 5916.5 8.490 8.419 10.605 40.667 0.246 118.783 94.292 -54.002
## 499 5917.0 8.490 8.103 10.333 38.969 0.228 123.407 96.778 -47.046
## 500 5917.5 8.490 7.825 9.997 37.522 0.213 127.794 100.026 -46.571
## 501 5918.0 8.490 7.562 9.766 36.375 0.204 132.237 102.400 -52.414
## 502 5918.5 8.490 7.287 9.669 35.001 0.202 137.234 103.422 -59.354
## 503 5919.0 8.490 7.063 9.594 32.748 0.200 141.574 104.236 -65.922
## 504 5919.5 8.490 6.950 9.516 30.390 0.199 143.879 105.088 -66.409
## 505 5920.0 8.490 6.886 9.467 28.841 0.196 145.228 105.635 -60.144
## 506 5920.5 8.490 6.813 9.426 27.273 0.192 146.778 106.086 -56.927
## 507 5921.0 8.490 6.735 9.386 24.993 0.188 148.482 106.542 -58.361
## 508 5921.5 8.490 6.668 9.401 22.872 0.183 149.976 106.366 -52.962
## 509 5922.0 8.490 6.632 9.475 21.973 0.179 150.787 105.543 -41.900
## 510 5922.5 8.490 6.611 9.547 22.164 0.179 151.272 104.749 -38.532
## 511 5923.0 8.490 6.571 9.618 22.547 0.185 152.174 103.971 -41.638
## 512 5923.5 8.490 6.535 9.725 22.890 0.197 153.018 102.831 -40.721
## 513 5924.0 8.490 6.532 9.842 23.339 0.210 153.085 101.605 -37.949
## 514 5924.5 8.490 6.587 9.950 24.493 0.219 151.825 100.501 -40.070
## 515 5925.0 8.490 6.674 10.104 25.666 0.222 149.831 98.970 -41.703
## 516 5925.5 8.490 6.764 10.354 25.963 0.223 147.837 96.582 -34.286
## 517 5926.0 8.490 6.902 10.690 25.668 0.224 144.888 93.548 -24.111
## 518 5927.0 8.490 7.409 11.332 26.325 0.231 134.980 88.247 -41.157
## 519 5927.5 8.490 7.658 11.699 27.115 0.238 130.584 85.478 -45.872
## 520 5928.5 8.490 8.226 12.716 26.075 0.243 121.559 78.640 -40.928
## 521 5929.0 8.490 8.486 13.112 27.835 0.245 117.848 76.267 -47.834
## 522 5929.5 8.490 8.668 13.397 30.262 0.244 115.365 74.645 -51.895
## 523 5930.0 8.490 8.830 13.653 30.844 0.242 113.248 73.244 -51.111
## 524 5930.5 8.490 9.049 13.894 30.980 0.241 110.508 71.976 -49.106
## 525 5931.0 8.490 9.298 14.101 32.179 0.246 107.550 70.918 -51.137
## 526 5931.5 8.490 9.485 14.276 34.124 0.251 105.432 70.046 -55.900
## 527 5932.0 8.490 9.609 14.415 35.553 0.254 104.072 69.374 -51.117
## 528 5932.5 8.490 9.722 14.509 36.109 0.253 102.863 68.923 -42.795
## 529 5933.0 8.490 9.872 14.643 36.130 0.250 101.294 68.292 -48.490
## 530 5933.5 8.490 10.087 14.891 36.562 0.250 99.136 67.154 -60.083
## 531 5934.0 8.490 10.369 15.253 37.828 0.251 96.444 65.561 -57.762
## 532 5935.0 8.490 11.156 16.392 40.223 0.250 89.640 61.004 -33.257
## 533 5935.5 8.490 11.675 17.175 40.992 0.250 85.655 58.224 -22.275
## 534 5936.0 8.490 12.257 17.993 42.252 0.251 81.590 55.578 -12.437
## 535 5936.5 8.489 12.920 18.854 42.624 0.251 77.400 53.039 -4.602
## 536 5937.0 8.514 13.738 19.889 41.677 0.254 72.790 50.279 -1.911
## 537 5937.5 8.540 14.757 21.181 40.877 0.260 67.766 47.213 -6.767
## 538 5938.0 8.514 15.859 22.577 42.150 0.266 63.055 44.293 -13.884
## 539 5938.5 8.489 16.838 23.779 44.049 0.270 59.389 42.054 -18.511
## 540 5939.0 8.490 17.562 24.586 43.929 0.271 56.940 40.674 -24.860
## 541 5939.5 8.490 18.033 25.019 41.379 0.268 55.454 39.969 -35.192
## 542 5940.0 8.490 18.347 25.210 38.675 0.258 54.503 39.666 -41.733
## 543 5940.5 8.490 18.672 25.287 36.692 0.247 53.556 39.546 -39.872
## 544 5941.0 8.490 19.050 25.300 35.042 0.243 52.494 39.525 -35.498
## 545 5941.5 8.490 19.296 25.210 33.704 0.245 51.823 39.667 -33.768
## 546 5942.0 8.490 19.272 24.950 33.169 0.247 51.887 40.080 -32.673
## 547 5942.5 8.490 19.126 24.584 34.177 0.248 52.284 40.678 -30.312
## 548 5943.0 8.490 19.105 24.294 36.542 0.250 52.341 41.163 -28.852
## 549 5944.0 8.490 19.567 24.548 39.054 0.251 51.107 40.737 -20.952
## 550 5944.5 8.490 19.889 25.093 38.500 0.253 50.278 39.851 -12.601
## 551 5945.0 8.490 20.454 25.787 39.981 0.254 48.891 38.779 -4.595
## 552 5945.5 8.490 21.205 26.403 42.803 0.257 47.159 37.875 -2.946
## 553 5946.0 8.490 21.868 26.384 43.609 0.259 45.729 37.902 -11.555
## 554 5946.5 8.490 22.644 26.090 41.897 0.257 44.162 38.328 -24.090
## 555 5947.0 8.490 23.660 26.820 40.345 0.258 42.266 37.286 -30.016
## 556 5947.5 8.490 24.547 28.766 40.890 0.264 40.739 34.763 -28.250
## 557 5948.0 8.490 25.193 30.116 42.344 0.271 39.694 33.205 -26.658
## 558 5948.5 8.490 25.804 29.874 42.444 0.279 38.754 33.474 -28.306
## 559 5949.0 8.490 26.202 29.022 41.392 0.283 38.165 34.457 -26.933
## 560 5949.5 8.490 26.421 28.804 40.876 0.284 37.848 34.717 -21.973
## 561 5950.0 8.489 26.833 29.266 41.036 0.284 37.268 34.169 -21.363
## 562 5950.5 8.514 27.490 30.052 41.028 0.284 36.376 33.275 -21.834
## 563 5951.0 8.513 28.273 30.913 40.608 0.284 35.369 32.349 -15.668
## 564 5951.5 8.497 29.337 31.725 40.406 0.283 34.086 31.521 -8.995
## 565 5952.0 8.531 30.577 32.447 40.898 0.281 32.705 30.820 -8.157
## 566 5952.5 8.542 31.668 33.142 41.437 0.279 31.577 30.174 -11.358
## 567 5953.0 8.530 32.571 33.936 41.261 0.277 30.702 29.467 -18.876
## 568 5953.5 8.497 33.489 34.905 40.607 0.275 29.860 28.649 -29.318
## 569 5954.0 8.498 34.404 35.967 40.285 0.273 29.066 27.803 -34.078
## 570 5954.5 8.546 35.076 37.020 40.741 0.268 28.510 27.012 -36.683
## 571 5955.0 8.550 35.456 38.119 42.206 0.265 28.204 26.234 -45.203
## 572 5955.5 8.511 36.089 39.388 43.531 0.264 27.709 25.389 -52.543
## 573 5956.0 8.514 37.578 40.909 43.762 0.268 26.611 24.444 -50.492
## 574 5956.5 8.515 39.940 42.840 43.825 0.272 25.037 23.342 -45.792
## 575 5957.0 8.489 43.021 45.322 44.583 0.272 23.244 22.064 -42.245
## 576 5957.5 8.489 46.541 48.245 45.759 0.270 21.486 20.728 -37.078
## 577 5958.0 8.513 50.386 51.428 47.869 0.271 19.847 19.445 -34.172
## 578 5958.5 8.523 54.522 54.970 50.639 0.273 18.341 18.192 -36.016
## 579 5959.5 8.531 65.146 64.702 49.860 0.276 15.350 15.455 -32.695
## 580 5960.0 8.508 72.859 72.423 47.227 0.280 13.725 13.808 -33.076
## 581 5960.5 8.521 83.422 84.713 45.037 0.282 11.987 11.805 -38.577
## 582 5961.0 8.499 99.302 104.097 44.344 0.282 10.070 9.606 -43.425
## 583 5961.5 8.512 126.253 132.141 46.356 0.281 7.921 7.568 -47.238
## 584 5962.0 8.540 166.941 169.172 49.354 0.283 5.990 5.911 -53.444
## 585 5962.5 8.514 218.810 216.730 50.819 0.282 4.570 4.614 -54.350
## 586 5963.0 8.489 276.837 273.133 50.504 0.280 3.612 3.661 -42.196
## 587 5963.5 8.488 337.482 330.002 49.784 0.278 2.963 3.030 -28.771
## 588 5964.0 8.498 396.153 380.129 48.829 0.273 2.524 2.631 -28.615
## 589 5964.5 8.531 451.672 422.377 47.916 0.272 2.214 2.368 -34.485
## 590 5965.0 8.557 507.850 457.204 48.177 0.273 1.969 2.187 -32.868
## 591 5965.5 8.523 559.204 485.141 49.811 0.271 1.788 2.061 -27.665
## 592 5966.0 8.487 602.761 508.549 51.001 0.266 1.659 1.966 -25.973
## 593 5966.5 8.488 637.662 531.306 50.313 0.256 1.568 1.882 -24.977
## 594 5967.0 8.524 665.292 557.416 47.451 0.239 1.503 1.794 -20.776
## 595 5967.5 8.571 687.231 586.643 43.313 0.224 1.455 1.705 -16.594
## 596 5968.0 8.547 705.502 617.035 39.586 0.224 1.417 1.621 -15.138
## 597 5968.5 8.522 721.618 645.029 37.971 0.238 1.386 1.550 -13.124
## 598 5969.0 8.547 734.683 667.113 38.252 0.254 1.361 1.499 -9.640
## 599 5969.5 8.524 745.811 681.135 38.428 0.260 1.341 1.468 -11.662
## 600 5970.0 8.512 756.048 688.806 37.893 0.260 1.323 1.452 -24.173
## 601 5970.5 8.514 764.641 693.755 37.856 0.263 1.308 1.441 -39.275
## 602 5971.0 8.496 769.484 698.172 38.064 0.270 1.300 1.432 -42.211
## 603 5971.5 8.557 769.272 702.321 37.876 0.276 1.300 1.424 -31.357
## 604 5972.0 8.557 764.677 706.202 37.666 0.279 1.308 1.416 -21.101
## 605 5972.5 8.495 757.882 710.433 37.647 0.278 1.319 1.408 -19.478
## 606 5973.0 8.521 751.484 715.100 37.027 0.275 1.331 1.398 -20.754
## 607 5973.5 8.580 747.943 719.703 36.583 0.274 1.337 1.390 -19.218
## 608 5974.0 8.590 748.166 724.318 37.766 0.272 1.337 1.381 -12.385
## 609 5974.5 8.565 749.961 729.308 41.098 0.273 1.333 1.371 -2.410
## 610 5975.0 8.553 750.096 732.594 44.709 0.275 1.333 1.365 0.878
## 611 5975.5 8.558 747.725 730.685 46.419 0.280 1.337 1.369 -9.478
## 612 5976.0 8.569 744.153 723.870 46.939 0.289 1.344 1.382 -25.715
## 613 5976.5 8.547 740.415 717.304 47.320 0.296 1.351 1.394 -33.724
## 614 5977.0 8.546 736.816 715.132 46.740 0.296 1.357 1.398 -28.413
## 615 5977.5 8.554 733.066 715.809 45.278 0.294 1.364 1.397 -16.811
## 616 5978.0 8.565 727.884 714.824 44.429 0.291 1.374 1.399 -12.303
## 617 5978.5 8.563 721.085 710.586 44.354 0.289 1.387 1.407 -18.652
## 618 5979.0 8.565 715.390 705.844 44.268 0.289 1.398 1.417 -22.090
## 619 5979.5 8.555 713.208 704.604 44.393 0.292 1.402 1.419 -13.015
## 620 5980.0 8.520 713.153 708.089 45.118 0.297 1.402 1.412 -1.294
## 621 5980.5 8.548 712.136 713.398 46.801 0.300 1.404 1.402 3.811
## 622 5981.0 8.547 708.904 716.668 49.061 0.300 1.411 1.395 3.932
## 623 5981.5 8.499 704.146 716.100 51.623 0.298 1.420 1.396 0.847
## 624 5982.0 8.512 698.580 710.998 54.552 0.296 1.431 1.406 -5.909
## 625 5982.5 8.538 691.916 700.026 56.957 0.292 1.445 1.429 -14.445
## 626 5983.0 8.523 683.400 682.709 57.644 0.287 1.463 1.465 -19.411
## 627 5983.5 8.545 673.568 661.210 57.222 0.280 1.485 1.512 -13.581
## 628 5984.0 8.535 662.300 638.983 57.568 0.271 1.510 1.565 0.291
## 629 5984.5 8.517 649.377 617.897 59.447 0.262 1.540 1.618 8.271
## 630 5985.0 8.533 636.177 598.710 61.089 0.257 1.572 1.670 1.599
## 631 5985.5 8.581 624.603 583.898 60.439 0.253 1.601 1.713 -12.357
## 632 5986.0 8.554 616.137 575.410 58.249 0.253 1.623 1.738 -23.154
## 633 5986.5 8.532 611.848 573.374 56.768 0.256 1.634 1.744 -30.655
## 634 5987.0 8.568 611.979 576.912 56.437 0.259 1.634 1.733 -34.697
## 635 5987.5 8.559 616.094 585.322 57.005 0.260 1.623 1.709 -32.236
## 636 5988.0 8.569 623.367 597.047 58.780 0.259 1.604 1.675 -27.445
## 637 5989.0 8.520 638.414 615.987 61.936 0.260 1.566 1.623 -27.796
## 638 5989.5 8.554 642.135 617.117 62.233 0.261 1.557 1.620 -19.615
## 639 5990.0 8.591 642.639 612.511 63.785 0.260 1.556 1.633 -12.492
## 640 5990.5 8.563 639.973 604.142 66.080 0.259 1.563 1.655 -17.712
## 641 5991.0 8.565 634.626 593.991 67.343 0.260 1.576 1.684 -29.664
## 642 5991.5 8.580 627.638 583.587 67.484 0.263 1.593 1.714 -33.979
## 643 5992.0 8.546 619.682 573.999 66.888 0.264 1.614 1.742 -28.905
## 644 5992.5 8.520 611.096 565.651 65.567 0.264 1.636 1.768 -25.866
## 645 5993.0 8.555 602.778 558.761 64.726 0.262 1.659 1.790 -29.997
## 646 5993.5 8.567 595.667 553.648 64.667 0.261 1.679 1.806 -32.206
## 647 5994.0 8.552 589.805 550.201 64.304 0.262 1.696 1.817 -26.579
## 648 5994.5 8.557 585.110 547.631 63.541 0.264 1.709 1.826 -20.024
## 649 5995.0 8.552 581.895 545.305 63.239 0.267 1.719 1.834 -19.148
## 650 5995.5 8.567 580.458 543.432 62.246 0.271 1.723 1.840 -21.516
## 651 5996.0 8.556 580.770 542.749 61.212 0.275 1.722 1.842 -23.533
## 652 5996.5 8.496 582.418 543.618 62.056 0.276 1.717 1.839 -22.461
## 653 5997.0 8.498 584.644 545.599 64.383 0.275 1.710 1.833 -16.544
## 654 5997.5 8.545 586.709 547.979 66.340 0.271 1.704 1.825 -9.798
## 655 5998.0 8.558 588.438 550.164 66.713 0.268 1.699 1.818 -8.519
## 656 5998.5 8.552 590.154 551.565 65.836 0.267 1.694 1.813 -9.987
## 657 5999.0 8.566 591.864 551.702 64.137 0.268 1.690 1.813 -10.594
## 658 5999.5 8.578 593.186 550.547 61.767 0.267 1.686 1.816 -12.505
## 659 6000.0 8.555 594.035 548.510 59.703 0.266 1.683 1.823 -17.665
## 660 6000.5 8.578 594.677 546.511 58.617 0.263 1.682 1.830 -24.788
## 661 6001.0 8.590 595.137 545.745 57.402 0.262 1.680 1.832 -31.124
## 662 6001.5 8.588 595.387 546.583 55.970 0.263 1.680 1.829 -31.230
## 663 6002.0 8.587 595.427 547.941 55.649 0.261 1.679 1.825 -24.447
## 664 6002.5 8.589 595.397 548.830 54.538 0.256 1.680 1.822 -18.422
## 665 6003.0 8.563 595.779 549.960 51.882 0.252 1.679 1.818 -18.812
## 666 6003.5 8.563 596.917 552.362 50.658 0.249 1.675 1.810 -21.204
## 667 6004.0 8.589 598.453 555.208 51.586 0.247 1.671 1.801 -17.447
## 668 6004.5 8.589 599.787 556.988 51.799 0.248 1.667 1.795 -9.581
## 669 6005.0 8.578 600.829 557.980 50.483 0.252 1.664 1.792 -6.622
## 670 6005.5 8.558 601.449 559.664 49.868 0.254 1.663 1.787 -8.757
## 671 6006.0 8.543 601.026 561.854 51.642 0.256 1.664 1.780 -6.444
## 672 6006.5 8.532 599.067 562.397 54.145 0.261 1.669 1.778 -0.279
## 673 6007.0 8.578 596.285 559.790 55.005 0.263 1.677 1.786 -2.316
## 674 6007.5 8.591 594.124 555.102 53.716 0.263 1.683 1.801 -13.920
## 675 6008.0 8.578 593.409 551.210 51.784 0.263 1.685 1.814 -23.793
## 676 6008.5 8.556 594.101 550.630 50.500 0.263 1.683 1.816 -27.059
## 677 6009.0 8.578 595.922 553.985 50.870 0.264 1.678 1.805 -23.900
## 678 6009.5 8.590 598.328 560.417 51.239 0.266 1.671 1.784 -15.789
## 679 6010.0 8.588 600.529 568.248 51.030 0.268 1.665 1.760 -10.792
## 680 6010.5 8.590 602.513 575.330 51.513 0.270 1.660 1.738 -14.848
## 681 6011.0 8.578 605.716 580.451 52.569 0.271 1.651 1.723 -21.727
## 682 6011.5 8.556 611.035 584.300 52.880 0.272 1.637 1.711 -20.425
## 683 6012.0 8.578 617.174 588.084 51.926 0.272 1.620 1.700 -12.469
## 684 6012.5 8.591 621.758 591.715 50.127 0.271 1.608 1.690 -9.270
## 685 6013.0 8.578 623.463 593.763 49.418 0.269 1.604 1.684 -14.581
## 686 6013.5 8.557 622.406 593.059 51.293 0.266 1.607 1.686 -21.319
## 687 6014.0 8.568 620.200 590.192 54.389 0.264 1.612 1.694 -23.699
## 688 6014.5 8.559 618.324 586.867 56.291 0.264 1.617 1.704 -22.139
## 689 6015.0 8.567 617.029 584.057 55.671 0.264 1.621 1.712 -18.550
## 690 6015.5 8.559 615.912 581.493 54.087 0.264 1.624 1.720 -12.974
## 691 6016.0 8.543 614.648 579.097 53.931 0.265 1.627 1.727 -8.459
## 692 6016.5 8.532 613.075 578.023 55.072 0.270 1.631 1.730 -12.642
## 693 6017.0 8.578 611.347 579.000 54.982 0.276 1.636 1.727 -20.495
## 694 6017.5 8.591 609.591 580.579 53.893 0.280 1.640 1.722 -23.764
## 695 6018.0 8.554 607.995 580.746 53.167 0.282 1.645 1.722 -26.520
## 696 6018.5 8.505 607.311 579.486 53.479 0.284 1.647 1.726 -29.818
## 697 6019.0 8.554 608.188 578.197 54.209 0.286 1.644 1.730 -29.195
## 698 6019.5 8.590 610.006 577.488 54.278 0.287 1.639 1.732 -29.486
## 699 6020.0 8.587 610.706 576.626 53.961 0.285 1.638 1.734 -32.541
## 700 6020.5 8.590 609.090 574.555 54.793 0.283 1.642 1.740 -31.111
## 701 6021.0 8.553 605.994 570.669 56.226 0.283 1.650 1.752 -28.238
## 702 6021.5 8.532 602.696 565.180 56.078 0.283 1.659 1.769 -31.419
## 703 6022.0 8.568 599.602 559.301 54.537 0.281 1.668 1.788 -35.355
## 704 6022.5 8.558 597.275 554.620 53.024 0.276 1.674 1.803 -35.034
## 705 6023.0 8.568 596.450 552.146 51.786 0.269 1.677 1.811 -36.007
## 706 6023.5 8.532 596.953 552.335 51.002 0.264 1.675 1.811 -39.099
## 707 6024.0 8.553 598.206 555.131 50.942 0.256 1.672 1.801 -37.488
## 708 6024.5 8.590 599.747 559.563 50.391 0.248 1.667 1.787 -31.862
## 709 6025.0 8.587 601.235 563.769 49.134 0.250 1.663 1.774 -30.657
## 710 6025.5 8.588 602.806 566.310 49.098 0.255 1.659 1.766 -34.961
## 711 6026.0 8.588 604.600 567.240 50.757 0.256 1.654 1.763 -35.552
## 712 6026.5 8.588 605.934 567.313 52.072 0.253 1.650 1.763 -29.677
## 713 6027.0 8.588 605.927 566.488 52.361 0.253 1.650 1.765 -27.228
## 714 6027.5 8.588 604.213 564.556 52.172 0.254 1.655 1.771 -32.319
## 715 6028.0 8.588 600.959 562.247 51.903 0.257 1.664 1.779 -36.077
## 716 6028.5 8.588 596.960 560.421 51.202 0.256 1.675 1.784 -35.012
## 717 6029.0 8.588 593.078 559.152 50.161 0.255 1.686 1.788 -34.816
## 718 6029.5 8.590 589.469 558.194 49.820 0.257 1.696 1.791 -36.364
## 719 6030.0 8.578 585.919 557.143 50.945 0.259 1.707 1.795 -37.779
## 720 6031.0 8.578 578.761 551.848 52.409 0.256 1.728 1.812 -46.955
## 721 6031.5 8.589 575.584 547.299 51.866 0.250 1.737 1.827 -51.829
## 722 6032.0 8.589 573.705 542.507 51.027 0.244 1.743 1.843 -50.910
## 723 6032.5 8.565 574.141 539.200 50.111 0.241 1.742 1.855 -40.365
## 724 6033.0 8.554 577.163 539.681 49.991 0.241 1.733 1.853 -28.428
## 725 6033.5 8.546 582.349 544.846 51.366 0.245 1.717 1.835 -29.523
## 726 6034.0 8.547 588.648 552.954 52.598 0.251 1.699 1.809 -39.411
## 727 6034.5 8.569 594.783 561.542 51.868 0.259 1.681 1.781 -40.235
## 728 6035.0 8.557 600.456 569.211 49.380 0.262 1.665 1.757 -32.025
## 729 6035.5 8.578 606.247 574.886 47.243 0.258 1.650 1.740 -26.510
## 730 6036.0 8.590 612.269 578.036 45.744 0.253 1.633 1.730 -23.803
## 731 6036.5 8.590 617.734 579.929 44.894 0.250 1.619 1.724 -20.428
## 732 6037.0 8.578 621.654 582.173 44.281 0.250 1.609 1.718 -22.960
## 733 6037.5 8.557 623.496 584.433 44.318 0.250 1.604 1.711 -32.947
## 734 6038.0 8.568 623.637 585.607 45.234 0.249 1.604 1.708 -42.481
## 735 6038.5 8.557 622.495 585.402 47.395 0.246 1.606 1.708 -48.265
## 736 6039.0 8.578 619.563 583.440 49.482 0.245 1.614 1.714 -48.208
## 737 6039.5 8.590 613.433 578.604 49.293 0.248 1.630 1.728 -37.795
## 738 6040.0 8.588 602.637 569.088 48.077 0.248 1.659 1.757 -25.444
## 739 6040.5 8.587 587.887 552.388 48.065 0.229 1.701 1.810 -25.980
## 740 6041.0 8.589 573.763 529.550 47.871 0.194 1.743 1.888 -30.846
## 741 6041.5 8.563 565.485 508.405 45.598 0.169 1.768 1.967 -24.801
## 742 6042.0 8.563 564.060 498.416 43.521 0.167 1.773 2.006 -18.588
## 743 6042.5 8.589 566.227 503.229 44.384 0.188 1.766 1.987 -20.538
## 744 6043.0 8.587 568.725 517.060 47.403 0.220 1.758 1.934 -16.884
## 745 6043.5 8.588 571.729 531.618 49.811 0.230 1.749 1.881 -7.577
## 746 6044.0 8.588 577.818 543.368 50.033 0.233 1.731 1.840 -11.793
## 747 6044.5 8.588 587.432 552.384 48.735 0.229 1.702 1.810 -28.611
## 748 6045.0 8.588 597.770 558.419 47.102 0.222 1.673 1.791 -39.347
## 749 6046.0 8.588 610.221 560.957 43.468 0.225 1.639 1.783 -40.730
## 750 6046.5 8.588 610.626 557.931 42.741 0.226 1.638 1.792 -39.458
## 751 6047.0 8.588 606.960 553.369 43.934 0.225 1.648 1.807 -35.013
## 752 6047.5 8.588 599.125 547.505 46.474 0.223 1.669 1.827 -35.235
## 753 6048.0 8.588 587.277 537.177 48.612 0.220 1.703 1.862 -41.119
## 754 6048.5 8.588 572.854 520.010 48.951 0.217 1.746 1.923 -43.393
## 755 6049.0 8.588 559.442 499.377 47.723 0.213 1.788 2.003 -40.341
## 756 6049.5 8.588 550.744 483.143 46.022 0.199 1.816 2.070 -37.440
## 757 6050.0 8.587 547.224 476.170 44.140 0.187 1.827 2.100 -34.133
## 758 6050.5 8.589 545.990 478.947 42.830 0.184 1.832 2.088 -30.865
## 759 6051.0 8.565 544.864 489.132 42.590 0.195 1.835 2.044 -32.391
## 760 6051.5 8.553 545.059 502.988 42.156 0.212 1.835 1.988 -40.406
## 761 6052.0 8.558 549.339 518.367 40.945 0.225 1.820 1.929 -50.012
## 762 6052.5 8.567 559.082 534.871 38.915 0.231 1.789 1.870 -48.335
## 763 6053.0 8.557 573.963 552.872 36.505 0.232 1.742 1.809 -32.029
## 764 6053.5 8.578 591.437 571.794 33.933 0.231 1.691 1.749 -19.896
## 765 6054.0 8.590 607.156 590.242 31.765 0.231 1.647 1.694 -20.994
## 766 6054.5 8.588 617.898 604.663 29.850 0.234 1.618 1.654 -19.375
## 767 6055.0 8.588 622.684 611.066 28.393 0.239 1.606 1.637 -13.692
## 768 6055.5 8.590 621.534 608.125 27.615 0.241 1.609 1.644 -18.773
## 769 6056.5 8.555 604.177 583.216 27.985 0.233 1.655 1.715 -35.844
## 770 6057.0 8.578 590.542 566.792 29.255 0.230 1.693 1.764 -39.164
## 771 6057.5 8.564 576.443 548.298 30.724 0.229 1.735 1.824 -46.166
## 772 6058.0 8.564 563.987 529.766 32.512 0.227 1.773 1.888 -47.891
## 773 6058.5 8.564 554.283 516.940 34.631 0.225 1.804 1.934 -41.178
## 774 6059.0 8.563 548.079 514.127 36.133 0.225 1.825 1.945 -35.110
## 775 6059.5 8.589 545.573 520.044 36.783 0.224 1.833 1.923 -33.169
## 776 6060.0 8.589 545.445 529.932 37.783 0.226 1.833 1.887 -32.250
## 777 6060.5 8.578 544.959 539.534 40.187 0.233 1.835 1.854 -33.188
## 778 6061.0 8.557 541.373 544.922 43.535 0.240 1.847 1.835 -36.794
## 779 6061.5 8.568 533.592 540.898 46.966 0.240 1.874 1.849 -40.180
## 780 6062.0 8.557 522.315 526.094 49.172 0.234 1.915 1.901 -38.141
## 781 6062.5 8.578 509.404 504.692 48.344 0.222 1.963 1.981 -30.156
## 782 6063.0 8.590 497.707 484.750 45.757 0.213 2.009 2.063 -25.733
## 783 6063.5 8.588 489.588 472.236 46.200 0.214 2.043 2.118 -28.291
## 784 6064.0 8.588 485.216 468.956 49.934 0.224 2.061 2.132 -26.182
## 785 6064.5 8.588 484.268 474.775 52.739 0.232 2.065 2.106 -18.151
## 786 6065.0 8.588 487.943 490.022 51.457 0.231 2.049 2.041 -17.266
## 787 6065.5 8.588 497.572 515.139 46.138 0.229 2.010 1.941 -21.465
## 788 6066.0 8.588 513.031 546.138 39.190 0.231 1.949 1.831 -19.714
## 789 6066.5 8.588 533.274 575.084 34.611 0.232 1.875 1.739 -16.493
## 790 6067.0 8.588 557.616 597.325 33.974 0.230 1.793 1.674 -21.926
## 791 6067.5 8.588 585.674 618.261 34.744 0.228 1.707 1.617 -33.361
## 792 6068.0 8.588 615.380 642.082 33.761 0.222 1.625 1.557 -39.288
## 793 6068.5 8.588 643.035 668.452 30.388 0.222 1.555 1.496 -35.202
## 794 6069.0 8.588 666.528 694.691 25.781 0.230 1.500 1.439 -29.636
## 795 6069.5 8.588 686.040 717.508 22.106 0.240 1.458 1.394 -28.959
## 796 6070.0 8.588 701.458 733.940 20.631 0.248 1.426 1.362 -27.243
## 797 6070.5 8.588 714.035 743.003 20.608 0.252 1.401 1.346 -26.745
## 798 6071.0 8.590 724.308 746.028 20.998 0.249 1.381 1.340 -33.053
## 799 6072.0 8.556 734.089 742.530 20.989 0.225 1.362 1.347 -3.286
## 800 6072.5 8.578 728.288 736.225 19.359 0.220 1.373 1.358 14.903
## 801 6073.0 8.590 716.002 725.496 17.681 0.219 1.397 1.378 2.252
## 802 6073.5 8.588 700.753 711.689 16.765 0.216 1.427 1.405 -19.110
## 803 6074.0 8.588 688.304 697.445 16.736 0.208 1.453 1.434 -30.495
## 804 6075.0 8.587 673.971 680.765 19.603 0.203 1.484 1.469 -40.182
## 805 6075.5 8.588 671.380 679.883 21.344 0.213 1.490 1.471 -36.595
## 806 6076.0 8.564 671.394 681.704 23.136 0.216 1.489 1.467 -31.856
## 807 6076.5 8.538 673.229 685.973 24.609 0.220 1.485 1.458 -27.785
## 808 6077.0 8.564 676.225 691.282 24.078 0.221 1.479 1.447 -23.920
## 809 6077.5 8.588 679.274 694.045 21.726 0.220 1.472 1.441 -24.067
## 810 6078.0 8.589 681.157 692.069 20.438 0.223 1.468 1.445 -28.500
## 811 6078.5 8.578 682.530 686.643 21.148 0.226 1.465 1.456 -31.086
## 812 6079.0 8.557 684.565 680.834 21.806 0.225 1.461 1.469 -35.283
## 813 6079.5 8.568 686.495 676.602 21.442 0.219 1.457 1.478 -49.898
## 814 6080.5 8.578 683.847 672.125 24.003 0.208 1.462 1.488 -33.714
## 815 6081.0 8.590 678.002 669.171 27.855 0.214 1.475 1.494 -4.808
## 816 6081.5 8.588 668.633 661.949 32.591 0.228 1.496 1.511 -4.727
## 817 6082.0 8.588 656.328 647.918 38.547 0.243 1.524 1.543 -21.390
## 818 6082.5 8.588 643.216 628.536 45.555 0.256 1.555 1.591 -31.597
## 819 6083.0 8.588 631.098 608.163 52.244 0.265 1.584 1.644 -36.109
## density.corr density phi.core k.core Facies X phi.core.frac
## 1 -0.033 2.205 33.9000 2442.5901 F1 NA 0.339000
## 2 -0.067 2.040 33.4131 3006.9888 F1 NA 0.334131
## 3 -0.064 1.888 33.1000 3370.0000 F1 NA 0.331000
## 4 -0.053 1.794 34.9000 2270.0000 F1 NA 0.349000
## 5 -0.054 1.758 35.0644 2530.7581 F1 NA 0.350644
## 6 -0.058 1.759 35.3152 2928.3137 F1 NA 0.353152
## 7 -0.056 1.781 35.6000 3380.0000 F1 NA 0.356000
## 8 -0.046 1.818 34.6448 3053.2048 F1 NA 0.346448
## 9 -0.040 1.848 33.7000 2730.0000 F1 NA 0.337000
## 10 -0.043 1.849 33.1980 2802.1687 F1 NA 0.331980
## 11 -0.047 1.834 32.7597 2865.1624 F1 NA 0.327597
## 12 -0.047 1.832 32.3215 2928.1562 F1 NA 0.323215
## 13 -0.046 1.845 31.4000 2960.0000 F1 NA 0.314000
## 14 -0.043 1.859 32.4996 2368.7905 F1 NA 0.324996
## 15 -0.041 1.868 33.9000 2550.4099 F1 NA 0.339000
## 16 -0.039 1.880 33.7292 2759.4919 F1 NA 0.337292
## 17 -0.040 1.892 33.5000 3040.0000 F1 NA 0.335000
## 18 -0.047 1.891 33.2520 2558.1506 F1 NA 0.332520
## 19 -0.049 1.877 32.9296 1931.9360 F1 NA 0.329296
## 20 -0.045 1.870 32.6000 1291.5699 F1 NA 0.326000
## 21 -0.041 1.877 34.3192 2155.4353 F1 NA 0.343192
## 22 -0.041 1.882 36.0000 3000.0000 F1 NA 0.360000
## 23 -0.043 1.873 34.6627 3066.8655 F1 NA 0.346627
## 24 -0.043 1.863 33.8000 3110.0000 F1 NA 0.338000
## 25 -0.043 1.868 33.2266 2686.7124 F1 NA 0.332266
## 26 -0.045 1.883 32.7943 2367.5498 F1 NA 0.327943
## 27 -0.046 1.887 32.5000 2150.3301 F1 NA 0.325000
## 28 -0.045 1.886 32.9036 2163.2437 F1 NA 0.329036
## 29 -0.036 1.900 33.2095 2173.0312 F1 NA 0.332095
## 30 -0.022 1.931 33.5154 2182.8186 F1 NA 0.335154
## 31 -0.018 1.953 33.8213 2192.6060 F1 NA 0.338213
## 32 -0.034 1.942 34.1272 2202.3936 F1 NA 0.341272
## 33 -0.050 1.906 34.5000 2214.3201 F1 NA 0.345000
## 34 -0.052 1.871 35.4259 2613.3105 F1 NA 0.354259
## 35 -0.049 1.849 36.3000 2990.0000 F1 NA 0.363000
## 36 -0.052 1.838 35.7830 2832.4385 F1 NA 0.357830
## 37 -0.056 1.837 35.3735 2707.6108 F1 NA 0.353735
## 38 -0.051 1.845 34.9000 2563.3101 F1 NA 0.349000
## 39 -0.044 1.853 34.7025 3090.0657 F1 NA 0.347025
## 40 -0.040 1.857 34.5000 3630.0000 F1 NA 0.345000
## 41 -0.035 1.869 32.4415 2531.0762 F1 NA 0.324415
## 42 -0.027 1.894 31.4000 1975.0400 F1 NA 0.314000
## 43 -0.022 1.920 31.0535 2147.4971 F1 NA 0.310535
## 44 -0.020 1.935 30.8000 2273.6499 F1 NA 0.308000
## 45 -0.022 1.944 30.6320 1712.4135 F1 NA 0.306320
## 46 -0.027 1.948 30.5000 1271.3800 F1 NA 0.305000
## 47 -0.035 1.936 23.9000 418.6400 F1 NA 0.239000
## 48 -0.042 1.911 27.0040 1362.4678 F1 NA 0.270040
## 49 -0.044 1.887 31.6000 2760.0000 F1 NA 0.316000
## 50 -0.045 1.875 31.4887 2602.4993 F1 NA 0.314887
## 51 -0.047 1.873 31.3000 2335.4399 F1 NA 0.313000
## 52 -0.048 1.879 30.9941 2495.1360 F1 NA 0.309941
## 53 -0.048 1.888 30.7000 2648.6399 F1 NA 0.307000
## 54 -0.046 1.896 29.5390 2463.9275 F1 NA 0.295390
## 55 -0.043 1.903 28.5027 2299.0537 F1 NA 0.285027
## 56 -0.038 1.911 27.6000 2155.4399 F1 NA 0.276000
## 57 -0.032 1.919 29.6946 2322.1902 F1 NA 0.296946
## 58 -0.029 1.923 31.3000 2450.0000 F1 NA 0.313000
## 59 -0.030 1.917 33.0000 2371.0400 F1 NA 0.330000
## 60 -0.032 1.910 32.2944 2049.1858 F1 NA 0.322944
## 61 -0.034 1.910 31.2000 1550.0200 F1 NA 0.312000
## 62 -0.036 1.916 31.4391 1722.9451 F1 NA 0.314391
## 63 -0.038 1.925 31.9000 2056.2000 F1 NA 0.319000
## 64 -0.038 1.930 31.7052 2023.9753 F1 NA 0.317052
## 65 -0.031 1.931 31.5001 1990.0415 F1 NA 0.315001
## 66 -0.025 1.930 31.2949 1956.1077 F1 NA 0.312949
## 67 -0.025 1.931 31.0000 1907.3199 F1 NA 0.310000
## 68 -0.027 1.936 30.7807 2196.3706 F1 NA 0.307807
## 69 -0.032 1.942 30.3000 2830.0000 F1 NA 0.303000
## 70 -0.036 1.947 30.8986 2697.3630 F1 NA 0.308986
## 71 -0.036 1.949 31.7000 2519.8000 F1 NA 0.317000
## 72 -0.033 1.949 31.4374 2274.8657 F1 NA 0.314374
## 73 -0.030 1.947 31.1674 2023.0345 F1 NA 0.311674
## 74 -0.029 1.943 31.0000 1866.9200 F1 NA 0.310000
## 75 -0.031 1.935 31.1000 2200.3501 F1 NA 0.311000
## 76 -0.035 1.924 31.2467 2067.3738 F1 NA 0.312467
## 77 -0.034 1.917 31.4000 1928.4800 F1 NA 0.314000
## 78 -0.023 1.916 31.1016 1789.1849 F1 NA 0.311016
## 79 -0.021 1.919 30.8000 1648.4301 F1 NA 0.308000
## 80 -0.027 1.923 30.9330 1866.0350 F1 NA 0.309330
## 81 -0.032 1.929 31.2000 2302.9199 F1 NA 0.312000
## 82 -0.036 1.934 31.1497 2225.8699 F1 NA 0.311497
## 83 -0.043 1.932 31.1000 2149.6299 F1 NA 0.311000
## 84 -0.048 1.926 30.4950 2276.3159 F1 NA 0.304950
## 85 -0.047 1.922 29.8000 2421.8501 F1 NA 0.298000
## 86 -0.040 1.919 29.9671 2427.4851 F1 NA 0.299671
## 87 -0.033 1.917 30.2393 2436.6628 F1 NA 0.302393
## 88 -0.026 1.917 30.5116 2445.8406 F1 NA 0.305116
## 89 -0.023 1.921 30.7838 2455.0183 F1 NA 0.307838
## 90 -0.025 1.922 31.0560 2464.1960 F1 NA 0.310560
## 91 -0.027 1.920 31.3282 2473.3740 F1 NA 0.313282
## 92 -0.030 1.916 31.7000 2485.9099 F1 NA 0.317000
## 93 -0.031 1.913 31.6364 2483.5156 F1 NA 0.316364
## 94 -0.030 1.911 31.5000 2478.3799 F1 NA 0.315000
## 95 -0.029 1.909 31.4013 2523.2039 F1 NA 0.314013
## 96 -0.027 1.909 31.2470 2593.2590 F1 NA 0.312470
## 97 -0.026 1.911 31.1000 2660.0000 F1 NA 0.311000
## 98 -0.028 1.913 31.2575 2638.9934 F1 NA 0.312575
## 99 -0.033 1.910 31.4000 2620.0000 F1 NA 0.314000
## 100 -0.036 1.904 31.0480 2423.1160 F1 NA 0.310480
## 101 -0.036 1.898 30.8000 2284.4299 F1 NA 0.308000
## 102 -0.037 1.896 30.9893 2011.7695 F1 NA 0.309893
## 103 -0.039 1.898 31.1000 1852.2700 F1 NA 0.311000
## 104 -0.038 1.903 29.0577 1467.6908 F1 NA 0.290577
## 105 -0.039 1.912 28.2000 1306.1700 F1 NA 0.282000
## 106 -0.039 1.926 15.8000 50.1500 F10 NA 0.158000
## 107 -0.030 1.952 18.6982 822.9766 F10 NA 0.186982
## 108 -0.021 1.985 22.9963 1969.0728 F10 NA 0.229963
## 109 -0.027 2.004 27.8000 3250.0000 F1 NA 0.278000
## 110 -0.036 2.007 26.7824 2448.0698 F1 NA 0.267824
## 111 -0.033 2.010 25.5000 1437.5200 F1 NA 0.255000
## 112 -0.028 2.027 24.7763 1641.8264 F1 NA 0.247763
## 113 -0.027 2.054 24.2000 1804.5400 F1 NA 0.242000
## 114 -0.019 2.083 21.3080 1040.1243 F1 NA 0.213080
## 115 -0.004 2.115 18.4000 271.4900 F2 NA 0.184000
## 116 0.009 2.148 17.5382 185.0957 F2 NA 0.175382
## 117 0.010 2.181 15.7000 0.8100 F2 NA 0.157000
## 118 0.003 2.210 16.2195 92.4887 F2 NA 0.162195
## 119 0.002 2.229 17.2452 273.4974 F2 NA 0.172452
## 120 0.014 2.237 18.2708 454.5060 F2 NA 0.182708
## 121 0.024 2.245 19.2965 635.5146 F2 NA 0.192965
## 122 0.023 2.262 20.2000 794.9600 F2 NA 0.202000
## 123 0.014 2.280 19.0000 193.4600 F10 NA 0.190000
## 124 0.007 2.286 18.1326 126.0047 F10 NA 0.181326
## 125 0.004 2.280 17.5000 76.8100 F10 NA 0.175000
## 126 0.004 2.277 17.5504 85.0097 F10 NA 0.175504
## 127 0.002 2.282 17.5884 91.1881 F10 NA 0.175884
## 128 -0.002 2.290 17.6264 97.3665 F10 NA 0.176264
## 129 -0.001 2.293 17.6644 103.5448 F10 NA 0.176644
## 130 0.006 2.289 17.7024 109.7232 F10 NA 0.177024
## 131 0.013 2.283 17.7404 115.9015 F10 NA 0.177404
## 132 0.014 2.280 17.7783 122.0799 F10 NA 0.177783
## 133 0.009 2.282 17.8163 128.2582 F10 NA 0.178163
## 134 0.006 2.287 17.8543 134.4366 F10 NA 0.178543
## 135 0.008 2.295 17.8923 140.6149 F10 NA 0.178923
## 136 0.007 2.299 17.9303 146.7933 F10 NA 0.179303
## 137 0.000 2.295 17.9683 152.9717 F10 NA 0.179683
## 138 0.000 2.286 18.0000 158.1300 F10 NA 0.180000
## 139 0.006 2.278 17.5326 116.5507 F10 NA 0.175326
## 140 0.008 2.268 17.2000 86.9600 F10 NA 0.172000
## 141 0.008 2.249 19.8420 63.8231 F10 NA 0.198420
## 142 0.010 2.230 22.6000 39.6700 F10 NA 0.226000
## 143 -0.002 2.224 26.0232 282.9963 F10 NA 0.260232
## 144 -0.033 2.212 30.5000 601.2100 F10 NA 0.305000
## 145 -0.053 2.169 29.7897 599.3371 F3 NA 0.297897
## 146 -0.038 2.113 29.0670 597.4316 F3 NA 0.290670
## 147 -0.013 2.092 28.3444 595.5261 F3 NA 0.283444
## 148 0.007 2.116 27.6217 593.6207 F3 NA 0.276217
## 149 0.015 2.152 26.8990 591.7152 F3 NA 0.268990
## 150 0.011 2.168 26.1764 589.8097 F3 NA 0.261764
## 151 0.004 2.163 25.6000 588.2900 F3 NA 0.256000
## 152 0.008 2.157 24.5062 522.3776 F3 NA 0.245062
## 153 0.016 2.171 23.5965 467.5622 F3 NA 0.235965
## 154 0.019 2.207 22.6869 412.7467 F3 NA 0.226869
## 155 0.012 2.244 21.7772 357.9313 F3 NA 0.217772
## 156 -0.001 2.265 20.8675 303.1158 F3 NA 0.208675
## 157 -0.005 2.271 19.9579 248.3004 F3 NA 0.199579
## 158 0.003 2.276 19.0000 190.5800 F3 NA 0.190000
## 159 0.012 2.285 19.0789 181.7682 F10 NA 0.190789
## 160 0.012 2.294 19.2000 168.2400 F10 NA 0.192000
## 161 0.009 2.296 19.2202 149.2137 F10 NA 0.192202
## 162 0.009 2.290 19.2572 114.3747 F10 NA 0.192572
## 163 0.008 2.271 19.3000 74.1400 F10 NA 0.193000
## 164 0.000 2.237 21.2929 146.0790 F10 NA 0.212929
## 165 -0.012 2.193 23.6510 231.2015 F10 NA 0.236510
## 166 -0.014 2.160 26.0091 316.3239 F10 NA 0.260091
## 167 0.001 2.160 28.5000 406.2400 F10 NA 0.285000
## 168 0.016 2.192 25.1195 308.4382 F3 NA 0.251195
## 169 0.010 2.229 21.5373 204.7999 F3 NA 0.215373
## 170 -0.009 2.231 19.3000 140.0700 F10 NA 0.193000
## 171 -0.027 2.191 27.2000 173.4400 F3 NA 0.272000
## 172 -0.027 2.143 22.7972 73.2072 F3 NA 0.227972
## 173 -0.011 2.136 19.6000 0.4200 F10 NA 0.196000
## 174 0.004 2.183 18.7028 2.2869 F10 NA 0.187028
## 175 0.007 2.249 18.0809 3.5809 F10 NA 0.180809
## 176 0.000 2.286 17.4591 4.8748 F10 NA 0.174591
## 177 -0.008 2.287 17.0000 5.8300 F10 NA 0.170000
## 178 -0.007 2.276 18.4000 35.8600 F10 NA 0.184000
## 179 0.007 2.266 18.3561 44.5030 F10 NA 0.183561
## 180 0.020 2.253 18.3000 55.5300 F10 NA 0.183000
## 181 0.012 2.220 21.4925 1599.2813 F10 NA 0.214925
## 182 -0.012 2.164 23.5000 2570.0000 F10 NA 0.235000
## 183 -0.022 2.118 23.0851 2294.7261 F3 NA 0.230851
## 184 -0.011 2.122 22.7761 2089.7009 F3 NA 0.227761
## 185 0.001 2.174 22.4671 1884.6757 F3 NA 0.224671
## 186 0.005 2.229 22.1581 1679.6505 F3 NA 0.221581
## 187 0.001 2.254 21.8491 1474.6252 F3 NA 0.218491
## 188 -0.002 2.256 21.5402 1269.6000 F3 NA 0.215402
## 189 0.000 2.251 21.2312 1064.5748 F3 NA 0.212312
## 190 0.006 2.247 20.9222 859.5496 F3 NA 0.209222
## 191 0.008 2.257 20.6132 654.5244 F3 NA 0.206132
## 192 0.003 2.283 20.3042 449.4991 F3 NA 0.203042
## 193 -0.001 2.305 19.9952 244.4739 F10 NA 0.199952
## 194 0.002 2.310 19.7000 48.6200 F10 NA 0.197000
## 195 0.006 2.306 19.7581 43.9438 F10 NA 0.197581
## 196 0.010 2.302 19.8138 39.4679 F10 NA 0.198138
## 197 0.014 2.305 19.8694 34.9919 F3 NA 0.198694
## 198 0.016 2.307 19.9000 32.5300 F3 NA 0.199000
## 199 0.015 2.290 19.9000 54.2100 F3 NA 0.199000
## 200 0.000 2.226 21.8858 906.6724 F3 NA 0.218858
## 201 -0.029 2.118 25.4446 2434.4473 F3 NA 0.254446
## 202 -0.046 2.014 30.0000 4390.0000 F3 NA 0.300000
## 203 -0.039 1.953 29.0486 4804.8022 F3 NA 0.290486
## 204 -0.030 1.946 27.5000 5480.0000 F3 NA 0.275000
## 205 -0.031 1.976 28.2000 4900.0000 F3 NA 0.282000
## 206 -0.030 2.013 27.9391 4786.5928 F3 NA 0.279391
## 207 -0.019 2.049 27.4209 4561.4106 F3 NA 0.274209
## 208 -0.007 2.100 26.9028 4336.2285 F10 NA 0.269028
## 209 -0.001 2.171 26.3846 4111.0464 F10 NA 0.263846
## 210 0.000 2.237 25.8665 3885.8645 F10 NA 0.258665
## 211 0.001 2.275 25.3483 3660.6824 F10 NA 0.253483
## 212 0.007 2.289 24.8302 3435.5005 F10 NA 0.248302
## 213 0.010 2.291 24.3120 3210.3184 F10 NA 0.243120
## 214 0.003 2.287 23.7939 2985.1362 F10 NA 0.237939
## 215 -0.001 2.280 23.2757 2759.9543 F10 NA 0.232757
## 216 0.007 2.275 22.7576 2534.7722 F10 NA 0.227576
## 217 0.009 2.270 22.2395 2309.5901 F10 NA 0.222395
## 218 0.002 2.268 21.7213 2084.4082 F10 NA 0.217213
## 219 0.001 2.272 21.2032 1859.2261 F10 NA 0.212032
## 220 0.005 2.286 20.6850 1634.0441 F10 NA 0.206850
## 221 0.004 2.303 20.1669 1408.8621 F10 NA 0.201669
## 222 0.006 2.311 19.6487 1183.6799 F10 NA 0.196487
## 223 0.013 2.306 19.1306 958.4979 F10 NA 0.191306
## 224 0.015 2.297 18.6124 733.3159 F10 NA 0.186124
## 225 0.008 2.287 18.0943 508.1339 F10 NA 0.180943
## 226 -0.002 2.263 17.5761 282.9518 F3 NA 0.175761
## 227 -0.011 2.220 17.3000 162.9400 F3 NA 0.173000
## 228 -0.015 2.181 23.1149 1109.5569 F3 NA 0.231149
## 229 -0.012 2.170 25.4000 1481.5601 F3 NA 0.254000
## 230 -0.005 2.190 20.8970 534.7041 F3 NA 0.208970
## 231 0.002 2.223 18.5000 30.6700 F3 NA 0.185000
## 232 0.007 2.252 18.6015 70.1081 F3 NA 0.186015
## 233 0.013 2.275 18.6832 101.8555 F3 NA 0.186832
## 234 0.014 2.291 18.7649 133.6028 F10 NA 0.187649
## 235 0.009 2.299 18.8466 165.3502 F10 NA 0.188466
## 236 0.007 2.300 18.9283 197.0975 F10 NA 0.189283
## 237 0.007 2.297 19.0100 228.8449 F10 NA 0.190100
## 238 0.005 2.292 19.0917 260.5923 F10 NA 0.190917
## 239 0.005 2.287 19.1734 292.3396 F10 NA 0.191734
## 240 0.008 2.287 19.2551 324.0869 F10 NA 0.192551
## 241 0.010 2.294 19.3368 355.8343 F10 NA 0.193368
## 242 0.013 2.303 19.4185 387.5817 F10 NA 0.194185
## 243 0.019 2.312 19.5002 419.3290 F10 NA 0.195002
## 244 0.025 2.318 19.5819 451.0764 F10 NA 0.195819
## 245 0.020 2.319 19.6636 482.8237 F10 NA 0.196636
## 246 0.008 2.315 19.7453 514.5711 F10 NA 0.197453
## 247 -0.001 2.305 19.8270 546.3184 F10 NA 0.198270
## 248 -0.003 2.293 19.9087 578.0658 F10 NA 0.199087
## 249 0.001 2.279 19.9904 609.8132 F10 NA 0.199904
## 250 0.009 2.264 20.0721 641.5605 F10 NA 0.200721
## 251 0.011 2.253 20.1538 673.3079 F10 NA 0.201538
## 252 0.004 2.248 20.2355 705.0552 F10 NA 0.202355
## 253 -0.001 2.246 20.3172 736.8026 F10 NA 0.203172
## 254 -0.001 2.244 20.3990 768.5499 F10 NA 0.203990
## 255 -0.002 2.239 20.4807 800.2973 F10 NA 0.204807
## 256 -0.003 2.231 20.5624 832.0446 F10 NA 0.205624
## 257 0.002 2.224 20.6441 863.7920 F10 NA 0.206441
## 258 0.012 2.220 20.7258 895.5394 F10 NA 0.207258
## 259 0.016 2.219 20.8075 927.2867 F10 NA 0.208075
## 260 0.010 2.221 20.8892 959.0341 F10 NA 0.208892
## 261 0.003 2.229 20.9709 990.7814 F10 NA 0.209709
## 262 -0.002 2.240 21.0526 1022.5287 F10 NA 0.210526
## 263 -0.007 2.254 21.1343 1054.2761 F10 NA 0.211343
## 264 -0.009 2.265 21.2160 1086.0234 F10 NA 0.212160
## 265 -0.011 2.269 21.2977 1117.7709 F10 NA 0.212977
## 266 -0.014 2.269 21.3794 1149.5182 F10 NA 0.213794
## 267 -0.011 2.270 21.4611 1181.2655 F10 NA 0.214611
## 268 -0.004 2.276 21.5428 1213.0129 F10 NA 0.215428
## 269 0.002 2.285 21.6245 1244.7603 F10 NA 0.216245
## 270 0.005 2.296 21.7062 1276.5076 F10 NA 0.217062
## 271 0.009 2.307 21.7879 1308.2550 F10 NA 0.217879
## 272 0.010 2.317 21.8696 1340.0023 F10 NA 0.218696
## 273 0.005 2.320 21.9513 1371.7496 F10 NA 0.219513
## 274 0.008 2.318 22.0330 1403.4971 F10 NA 0.220330
## 275 0.023 2.317 22.1147 1435.2444 F10 NA 0.221147
## 276 0.029 2.319 22.1964 1466.9917 F10 NA 0.221964
## 277 0.019 2.316 22.2781 1498.7391 F10 NA 0.222781
## 278 0.003 2.301 22.3598 1530.4865 F10 NA 0.223598
## 279 -0.008 2.272 22.4415 1562.2338 F10 NA 0.224415
## 280 -0.007 2.243 22.5000 1584.9600 F5 NA 0.225000
## 281 0.006 2.230 20.4237 1066.3792 F5 NA 0.204237
## 282 0.009 2.227 18.8068 662.5491 F5 NA 0.188068
## 283 -0.002 2.219 17.7000 386.1200 F10 NA 0.177000
## 284 -0.011 2.199 21.2844 1821.4403 F10 NA 0.212844
## 285 -0.017 2.169 22.9000 2468.4099 F5 NA 0.229000
## 286 -0.021 2.121 24.0280 2346.7214 F5 NA 0.240280
## 287 -0.024 2.062 24.6000 2285.0200 F5 NA 0.246000
## 288 -0.026 2.015 26.3099 4135.5439 F5 NA 0.263099
## 289 -0.027 1.996 27.7000 5640.0000 F5 NA 0.277000
## 290 -0.024 2.001 25.6304 3580.1563 F5 NA 0.256304
## 291 -0.024 2.011 23.1000 1061.7000 F5 NA 0.231000
## 292 -0.028 2.003 24.4103 2019.7881 F5 NA 0.244103
## 293 -0.032 1.976 25.9823 3169.1899 F5 NA 0.259823
## 294 -0.034 1.948 27.5543 4318.5918 F5 NA 0.275543
## 295 -0.033 1.932 29.1262 5467.9937 F5 NA 0.291262
## 296 -0.031 1.920 30.1000 6180.0000 F5 NA 0.301000
## 297 -0.033 1.904 30.2302 6844.0718 F5 NA 0.302302
## 298 -0.037 1.886 30.3000 7200.0000 F5 NA 0.303000
## 299 -0.037 1.871 31.2000 8390.0000 F5 NA 0.312000
## 300 -0.034 1.865 30.9850 7956.4258 F5 NA 0.309850
## 301 -0.031 1.871 30.7673 7517.4834 F5 NA 0.307673
## 302 -0.025 1.894 30.6000 7180.0000 F5 NA 0.306000
## 303 -0.015 1.931 28.8000 562.5400 F5 NA 0.288000
## 304 -0.007 1.971 29.4052 1348.7238 F5 NA 0.294052
## 305 -0.007 2.001 30.5371 2818.8896 F5 NA 0.305371
## 306 -0.006 2.023 31.2000 3680.0000 F5 NA 0.312000
## 307 -0.004 2.045 27.3008 2216.6179 F5 NA 0.273008
## 308 -0.005 2.068 23.6000 827.6600 F5 NA 0.236000
## 309 -0.005 2.086 25.0818 1538.3466 F5 NA 0.250818
## 310 0.000 2.095 27.9000 2890.0000 F5 NA 0.279000
## 311 0.003 2.092 27.9000 2383.2690 F5 NA 0.279000
## 312 -0.002 2.084 27.9000 2029.4900 F5 NA 0.279000
## 313 -0.007 2.076 27.6015 3820.7578 F5 NA 0.276015
## 314 -0.008 2.072 27.3000 5630.0000 F5 NA 0.273000
## 315 -0.006 2.069 26.8606 5202.5576 F5 NA 0.268606
## 316 -0.004 2.069 26.2000 4560.0000 F5 NA 0.262000
## 317 -0.005 2.071 27.5406 6232.8345 F5 NA 0.275406
## 318 -0.008 2.072 28.5000 7430.0000 F5 NA 0.285000
## 319 -0.014 2.070 27.5435 6186.6069 F5 NA 0.275435
## 320 -0.020 2.069 26.5000 4830.0000 F5 NA 0.265000
## 321 -0.021 2.073 27.6898 5338.7207 F5 NA 0.276898
## 322 -0.022 2.075 29.4000 6070.0000 F5 NA 0.294000
## 323 -0.023 2.071 28.7972 6447.5181 F5 NA 0.287972
## 324 -0.023 2.063 28.1080 6879.2051 F5 NA 0.281080
## 325 -0.019 2.059 27.5000 7260.0000 F5 NA 0.275000
## 326 -0.015 2.063 26.3578 5067.7798 F5 NA 0.263578
## 327 -0.015 2.068 24.9000 2270.0000 F5 NA 0.249000
## 328 -0.017 2.069 25.7652 1917.3143 F5 NA 0.257652
## 329 -0.019 2.067 27.2743 1302.1428 F5 NA 0.272743
## 330 -0.021 2.062 28.1000 965.5400 F5 NA 0.281000
## 331 -0.026 2.053 27.7692 2610.9341 F5 NA 0.277692
## 332 -0.026 2.041 27.5416 3743.4775 F5 NA 0.275416
## 333 -0.020 2.029 27.3139 4876.0210 F5 NA 0.273139
## 334 -0.015 2.025 27.0862 6008.5645 F5 NA 0.270862
## 335 -0.014 2.033 26.8586 7141.1079 F5 NA 0.268586
## 336 -0.013 2.051 26.7000 7930.0000 F5 NA 0.267000
## 337 -0.012 2.070 28.2026 8742.7529 F5 NA 0.282026
## 338 -0.012 2.083 28.9000 9120.0000 F5 NA 0.289000
## 339 -0.015 2.086 26.7071 9898.4785 F5 NA 0.267071
## 340 -0.018 2.089 24.9000 10540.0000 F5 NA 0.249000
## 341 -0.021 2.093 25.0203 9533.3623 F5 NA 0.250203
## 342 -0.026 2.096 25.2000 8030.0000 F5 NA 0.252000
## 343 -0.028 2.092 27.5236 6911.2437 F5 NA 0.275236
## 344 -0.018 2.082 30.6000 5430.0000 F5 NA 0.306000
## 345 -0.010 2.074 29.7470 5048.1919 F5 NA 0.297470
## 346 -0.014 2.066 28.9217 4678.7793 F5 NA 0.289217
## 347 -0.017 2.058 28.5000 4490.0000 F5 NA 0.285000
## 348 -0.009 2.052 31.1000 3840.0000 F5 NA 0.311000
## 349 0.001 2.052 29.7170 2968.5474 F5 NA 0.297170
## 350 0.003 2.059 27.4000 1508.5300 F5 NA 0.274000
## 351 -0.004 2.070 28.2452 2100.5769 F5 NA 0.282452
## 352 -0.008 2.087 29.5028 2981.4578 F5 NA 0.295028
## 353 -0.005 2.109 30.6000 3750.0000 F5 NA 0.306000
## 354 -0.005 2.134 27.9413 7119.8560 F5 NA 0.279413
## 355 -0.010 2.153 26.6000 8820.0000 F5 NA 0.266000
## 356 -0.014 2.156 27.2000 2032.8934 F5 NA 0.272000
## 357 -0.010 2.145 27.2000 1201.6453 F5 NA 0.272000
## 358 -0.003 2.138 27.2000 226.0300 F5 NA 0.272000
## 359 0.001 2.147 23.3897 131.3576 F3 NA 0.233897
## 360 -0.001 2.166 18.4000 7.3800 F3 NA 0.184000
## 361 -0.006 2.179 20.8398 397.6351 F10 NA 0.208398
## 362 -0.010 2.182 24.6000 999.0900 F3 NA 0.246000
## 363 -0.009 2.184 24.9497 841.6011 F3 NA 0.249497
## 364 -0.004 2.195 25.5470 572.5554 F3 NA 0.255470
## 365 -0.003 2.213 26.1444 303.5096 F3 NA 0.261444
## 366 -0.006 2.228 26.5000 143.3300 F3 NA 0.265000
## 367 -0.003 2.237 25.0778 119.7091 F3 NA 0.250778
## 368 0.003 2.238 24.0652 102.8927 F10 NA 0.240652
## 369 0.003 2.233 23.0527 86.0763 F10 NA 0.230527
## 370 0.004 2.230 22.0402 69.2599 F10 NA 0.220402
## 371 0.010 2.237 21.0276 52.4436 F10 NA 0.210276
## 372 0.014 2.249 20.0151 35.6272 F10 NA 0.200151
## 373 0.007 2.248 19.2000 22.0900 F10 NA 0.192000
## 374 -0.004 2.226 20.4398 759.7528 F10 NA 0.204398
## 375 -0.014 2.182 21.4773 1377.0441 F10 NA 0.214773
## 376 -0.014 2.123 22.5148 1994.3353 F10 NA 0.225148
## 377 -0.006 2.069 23.6000 2640.0000 F10 NA 0.236000
## 378 -0.001 2.034 26.1195 3427.3506 F7 NA 0.261195
## 379 -0.004 2.017 29.2000 4390.0000 F7 NA 0.292000
## 380 -0.007 2.010 30.0648 3882.9058 F8 NA 0.300648
## 381 -0.005 2.009 31.4000 3100.0000 F8 NA 0.314000
## 382 -0.003 2.014 31.3580 3340.3401 F8 NA 0.313580
## 383 -0.007 2.021 31.2990 3677.3889 F8 NA 0.312990
## 384 -0.013 2.026 31.2401 4014.4380 F8 NA 0.312401
## 385 -0.014 2.029 31.2000 4243.5298 F8 NA 0.312000
## 386 -0.011 2.028 31.0132 3936.2375 F8 NA 0.310132
## 387 -0.010 2.024 30.9000 3750.0000 F8 NA 0.309000
## 388 -0.010 2.021 31.1000 3700.0000 F8 NA 0.311000
## 389 -0.008 2.019 31.2534 3181.6086 F8 NA 0.312534
## 390 -0.006 2.022 31.4677 2457.0735 F8 NA 0.314677
## 391 -0.006 2.028 31.6000 2010.0000 F8 NA 0.316000
## 392 -0.006 2.032 30.9478 2805.6685 F8 NA 0.309478
## 393 -0.008 2.031 30.6000 3230.0000 F8 NA 0.306000
## 394 -0.012 2.027 30.8646 3302.7673 F8 NA 0.308646
## 395 -0.019 2.023 31.0000 3340.0000 F8 NA 0.310000
## 396 -0.023 2.019 30.6807 2963.2549 F8 NA 0.306807
## 397 -0.019 2.015 30.5000 2750.0000 F8 NA 0.305000
## 398 -0.012 2.015 31.3144 2947.7891 F8 NA 0.313144
## 399 -0.008 2.017 31.9000 3090.0000 F8 NA 0.319000
## 400 -0.007 2.018 31.6445 3110.4392 F8 NA 0.316445
## 401 -0.006 2.017 31.4150 3128.8020 F8 NA 0.314150
## 402 -0.007 2.017 31.1854 3147.1648 F8 NA 0.311854
## 403 -0.010 2.020 30.9000 3170.0000 F8 NA 0.309000
## 404 -0.014 2.024 30.9840 3033.0540 F8 NA 0.309840
## 405 -0.014 2.032 31.1000 2844.1299 F8 NA 0.311000
## 406 -0.010 2.039 30.5261 2137.3313 F8 NA 0.305261
## 407 -0.003 2.046 29.9000 1366.1600 F8 NA 0.299000
## 408 0.004 2.055 30.0000 1479.3800 F8 NA 0.300000
## 409 0.004 2.071 27.7307 1291.2828 F8 NA 0.277307
## 410 -0.001 2.099 24.7307 1042.6234 F8 NA 0.247307
## 411 -0.006 2.137 20.4000 683.6700 F7 NA 0.204000
## 412 -0.008 2.176 20.6782 815.7291 F7 NA 0.206782
## 413 -0.018 2.195 21.1782 1053.0554 F7 NA 0.211782
## 414 -0.028 2.184 21.6782 1290.3817 F7 NA 0.216782
## 415 -0.019 2.163 22.3000 1585.5100 F7 NA 0.223000
## 416 -0.003 2.162 22.0492 1510.6265 F7 NA 0.220492
## 417 0.008 2.191 21.7176 1411.6324 F7 NA 0.217176
## 418 0.016 2.240 21.3860 1312.6384 F10 NA 0.213860
## 419 0.022 2.292 21.0544 1213.6443 F10 NA 0.210544
## 420 0.016 2.329 20.7228 1114.6503 F10 NA 0.207228
## 421 0.006 2.340 20.3912 1015.6563 F10 NA 0.203912
## 422 0.008 2.329 20.0596 916.6622 F10 NA 0.200596
## 423 0.015 2.316 19.7280 817.6682 F10 NA 0.197280
## 424 0.018 2.311 19.3965 718.6742 F10 NA 0.193965
## 425 0.015 2.310 19.0649 619.6802 F10 NA 0.190649
## 426 0.012 2.309 18.7333 520.6862 F10 NA 0.187333
## 427 0.011 2.306 18.4017 421.6921 F10 NA 0.184017
## 428 0.013 2.302 18.0701 322.6981 F10 NA 0.180701
## 429 0.014 2.300 17.7385 223.7040 F10 NA 0.177385
## 430 0.011 2.303 17.4069 124.7100 F10 NA 0.174069
## 431 0.001 2.306 17.0000 3.2300 F10 NA 0.170000
## 432 -0.005 2.304 17.3509 33.7340 F10 NA 0.173509
## 433 -0.003 2.300 17.8050 73.2033 F10 NA 0.178050
## 434 0.008 2.299 18.2591 112.6725 F10 NA 0.182591
## 435 0.012 2.304 18.7132 152.1418 F10 NA 0.187132
## 436 0.005 2.307 19.1672 191.6111 F10 NA 0.191672
## 437 0.006 2.305 19.6213 231.0803 F10 NA 0.196213
## 438 0.020 2.306 20.0754 270.5496 F10 NA 0.200754
## 439 0.026 2.321 20.5295 310.0188 F10 NA 0.205295
## 440 0.023 2.342 20.9836 349.4881 F10 NA 0.209836
## 441 0.009 2.337 21.4376 388.9573 F10 NA 0.214376
## 442 0.016 2.294 21.8917 428.4266 F10 NA 0.218917
## 443 0.062 2.249 22.3458 467.8958 F10 NA 0.223458
## 444 0.089 2.240 22.7999 507.3651 F10 NA 0.227999
## 445 0.057 2.275 23.2540 546.8344 F10 NA 0.232540
## 446 0.021 2.318 23.7080 586.3036 F10 NA 0.237080
## 447 0.033 2.335 24.1621 625.7729 F10 NA 0.241621
## 448 0.047 2.334 24.6162 665.2421 F10 NA 0.246162
## 449 0.032 2.332 25.0703 704.7114 F10 NA 0.250703
## 450 0.009 2.335 25.5243 744.1807 F10 NA 0.255243
## 451 0.006 2.347 25.9784 783.6499 F10 NA 0.259784
## 452 0.008 2.361 26.4325 823.1191 F10 NA 0.264325
## 453 0.007 2.372 26.8866 862.5884 F10 NA 0.268866
## 454 0.012 2.381 27.3407 902.0577 F10 NA 0.273407
## 455 0.020 2.387 27.7947 941.5269 F10 NA 0.277947
## 456 0.018 2.386 28.2488 980.9962 F10 NA 0.282488
## 457 0.007 2.372 28.7029 1020.4655 F10 NA 0.287029
## 458 -0.002 2.342 29.1570 1059.9347 F10 NA 0.291570
## 459 -0.002 2.300 29.6110 1099.4039 F10 NA 0.296110
## 460 -0.006 2.197 30.5192 1178.3425 F10 NA 0.305192
## 461 -0.017 2.137 30.9733 1217.8118 F10 NA 0.309733
## 462 -0.021 2.084 31.4274 1257.2810 F10 NA 0.314274
## 463 -0.014 2.051 31.7000 1280.9800 F8 NA 0.317000
## 464 -0.006 2.038 31.3508 1380.1622 F8 NA 0.313508
## 465 -0.012 2.031 31.0000 1479.8101 F8 NA 0.310000
## 466 -0.023 2.020 31.3363 1574.8315 F8 NA 0.313363
## 467 -0.024 2.003 32.1000 1790.6000 F8 NA 0.321000
## 468 -0.018 1.985 32.3683 2417.5913 F8 NA 0.323683
## 469 -0.018 1.973 32.9000 3660.0000 F8 NA 0.329000
## 470 -0.021 1.971 32.8747 4203.3662 F8 NA 0.328747
## 471 -0.018 1.980 32.8391 4969.6675 F8 NA 0.328391
## 472 -0.011 1.995 32.8000 5810.0000 F8 NA 0.328000
## 473 -0.008 2.010 30.7071 4703.0840 F8 NA 0.307071
## 474 -0.007 2.025 28.3000 3430.0000 F8 NA 0.283000
## 475 -0.002 2.039 29.4132 4832.6045 F8 NA 0.294132
## 476 0.006 2.048 30.3000 5950.0000 F8 NA 0.303000
## 477 0.007 2.050 30.3880 6389.9697 F8 NA 0.303880
## 478 -0.009 2.040 30.5000 6950.0000 F8 NA 0.305000
## 479 -0.013 2.032 30.5000 7862.0825 F8 NA 0.305000
## 480 -0.010 2.026 30.5000 8190.0000 F8 NA 0.305000
## 481 -0.006 2.025 32.3000 7020.0000 F8 NA 0.323000
## 482 -0.006 2.026 32.2698 6917.3823 F8 NA 0.322698
## 483 -0.009 2.026 32.2000 6680.0000 F8 NA 0.322000
## 484 -0.011 2.023 32.0434 6388.7993 F8 NA 0.320434
## 485 -0.009 2.022 31.7000 5750.0000 F8 NA 0.317000
## 486 -0.009 2.022 31.8206 5412.3223 F8 NA 0.318206
## 487 -0.010 2.023 31.9839 4954.9937 F8 NA 0.319839
## 488 -0.011 2.025 32.1000 4630.0000 F8 NA 0.321000
## 489 -0.010 2.023 32.0426 4451.9521 F8 NA 0.320426
## 490 -0.010 2.020 32.0000 4320.0000 F8 NA 0.320000
## 491 -0.011 2.016 31.7157 4047.0544 F8 NA 0.317157
## 492 -0.014 2.014 31.5000 3840.0000 F8 NA 0.315000
## 493 -0.016 2.012 31.7630 3872.8757 F8 NA 0.317630
## 494 -0.015 2.009 31.9000 3890.0000 F8 NA 0.319000
## 495 -0.014 2.008 31.9000 3997.4805 F8 NA 0.319000
## 496 -0.014 2.007 31.9000 4075.8799 F8 NA 0.319000
## 497 -0.012 2.010 31.9000 4154.2788 F8 NA 0.319000
## 498 -0.006 2.024 31.9000 4210.0000 F8 NA 0.319000
## 499 -0.001 2.046 30.6000 2520.0000 F8 NA 0.306000
## 500 0.002 2.067 30.1362 4328.6606 F8 NA 0.301362
## 501 0.003 2.078 29.7007 6027.3105 F8 NA 0.297007
## 502 -0.005 2.076 29.2651 7725.9600 F8 NA 0.292651
## 503 -0.020 2.069 29.0000 8760.0000 F5 NA 0.290000
## 504 -0.025 2.062 29.7000 7740.0000 F5 NA 0.297000
## 505 -0.018 2.055 29.1759 8306.0459 F5 NA 0.291759
## 506 -0.011 2.054 28.7000 8820.0000 F5 NA 0.287000
## 507 -0.010 2.065 28.7920 7918.8984 F5 NA 0.287920
## 508 -0.012 2.086 28.9000 6860.0000 F5 NA 0.289000
## 509 -0.016 2.104 28.4025 6171.7534 F5 NA 0.284025
## 510 -0.021 2.111 27.7000 5200.0000 F5 NA 0.277000
## 511 -0.018 2.103 27.8919 8820.1025 F5 NA 0.278919
## 512 -0.012 2.084 28.0000 10860.0000 F5 NA 0.280000
## 513 -0.011 2.058 28.2202 6697.7793 F5 NA 0.282202
## 514 -0.015 2.036 28.3000 5190.0000 F8 NA 0.283000
## 515 -0.020 2.024 29.3094 5363.0371 F8 NA 0.293094
## 516 -0.018 2.023 29.9874 5479.2744 F8 NA 0.299874
## 517 -0.009 2.026 30.6655 5595.5122 F8 NA 0.306655
## 518 0.003 2.023 31.4848 5963.4404 F8 NA 0.314848
## 519 0.002 2.019 31.9000 6280.0000 F8 NA 0.319000
## 520 -0.004 2.014 31.7589 6138.8628 F8 NA 0.317589
## 521 -0.012 2.014 31.6668 6046.8418 F8 NA 0.316668
## 522 -0.013 2.017 31.5748 5954.8203 F8 NA 0.315748
## 523 -0.006 2.021 31.5000 5880.0000 F8 NA 0.315000
## 524 0.001 2.025 31.1219 5266.6743 F8 NA 0.311219
## 525 0.002 2.028 30.8034 4749.9390 F8 NA 0.308034
## 526 -0.001 2.031 30.6000 4420.0000 F8 NA 0.306000
## 527 -0.008 2.036 30.5374 4119.3125 F8 NA 0.305374
## 528 -0.010 2.039 30.5000 3940.0000 F8 NA 0.305000
## 529 -0.006 2.043 30.5000 4011.0640 F8 NA 0.305000
## 530 -0.003 2.046 30.5000 4070.0000 F8 NA 0.305000
## 531 -0.003 2.047 30.5519 4267.1182 F8 NA 0.305519
## 532 0.002 2.043 30.7000 3970.0000 F8 NA 0.307000
## 533 -0.003 2.043 30.7000 3982.3992 F8 NA 0.307000
## 534 -0.009 2.043 30.7000 3998.8315 F8 NA 0.307000
## 535 -0.010 2.044 30.7000 4020.0000 F8 NA 0.307000
## 536 -0.008 2.047 30.4053 3520.5999 F8 NA 0.304053
## 537 -0.008 2.048 29.8000 2495.1101 F8 NA 0.298000
## 538 -0.005 2.046 30.3945 2126.4495 F8 NA 0.303945
## 539 0.002 2.042 31.4988 1441.6909 F8 NA 0.314988
## 540 0.004 2.041 32.2000 1006.8500 F8 NA 0.322000
## 541 -0.002 2.042 29.5483 884.5511 F8 NA 0.295483
## 542 -0.009 2.044 28.4000 831.5900 F8 NA 0.284000
## 543 -0.012 2.047 29.7962 2790.4949 F8 NA 0.297962
## 544 -0.010 2.051 31.2000 4760.0000 F8 NA 0.312000
## 545 -0.007 2.056 30.5736 3950.7856 F8 NA 0.305736
## 546 -0.004 2.058 29.1000 2047.1400 F8 NA 0.291000
## 547 -0.004 2.060 29.5330 2114.7256 F8 NA 0.295330
## 548 -0.003 2.061 30.3000 2234.4399 F8 NA 0.303000
## 549 0.001 2.061 30.3000 3956.0886 F8 NA 0.303000
## 550 -0.004 2.056 30.3000 4810.0000 F8 NA 0.303000
## 551 -0.009 2.050 30.7348 3983.7849 F8 NA 0.307348
## 552 -0.008 2.049 31.1000 3290.0000 F8 NA 0.311000
## 553 -0.004 2.058 30.0246 2250.9197 F8 NA 0.300246
## 554 -0.004 2.072 29.2000 1454.2400 F8 NA 0.292000
## 555 -0.008 2.078 28.4938 2423.3625 F8 NA 0.284938
## 556 -0.008 2.076 27.6000 3650.0000 F8 NA 0.276000
## 557 -0.005 2.073 28.4051 3328.5642 F8 NA 0.284051
## 558 -0.004 2.068 30.5000 2492.1201 F8 NA 0.305000
## 559 -0.001 2.060 30.8001 2698.5298 F8 NA 0.308001
## 560 0.001 2.055 31.5000 3180.0000 F8 NA 0.315000
## 561 -0.004 2.054 31.2625 3293.4705 F8 NA 0.312625
## 562 -0.012 2.054 30.8861 3473.3303 F8 NA 0.308861
## 563 -0.014 2.051 30.6000 3610.0000 F8 NA 0.306000
## 564 -0.008 2.044 29.7000 1181.8900 F8 NA 0.297000
## 565 -0.004 2.039 29.9200 1652.2738 F8 NA 0.299200
## 566 -0.007 2.036 30.3588 2590.4043 F8 NA 0.303588
## 567 -0.012 2.033 30.7000 3320.0000 F8 NA 0.307000
## 568 -0.018 2.028 29.3560 2433.3545 F8 NA 0.293560
## 569 -0.021 2.021 28.5000 1868.6801 F8 NA 0.285000
## 570 -0.017 2.016 30.3995 1899.3845 F8 NA 0.303995
## 571 -0.015 2.014 31.3000 1913.9399 F8 NA 0.313000
## 572 -0.014 2.014 31.9000 3405.0000 F8 NA 0.319000
## 573 -0.011 2.018 31.9205 3385.5239 F8 NA 0.319205
## 574 -0.010 2.023 31.9455 3361.7825 F8 NA 0.319455
## 575 -0.014 2.026 31.9705 3338.0410 F8 NA 0.319705
## 576 -0.015 2.024 32.0000 3310.0000 F8 NA 0.320000
## 577 -0.009 2.020 31.9488 2997.9072 F8 NA 0.319488
## 578 -0.002 2.019 31.9000 2700.0000 F8 NA 0.319000
## 579 -0.005 2.022 31.9000 2913.8325 F8 NA 0.319000
## 580 -0.016 2.021 31.9000 2970.0000 F8 NA 0.319000
## 581 -0.022 2.023 31.1272 3150.3203 F8 NA 0.311272
## 582 -0.021 2.030 30.7000 3250.0000 F8 NA 0.307000
## 583 -0.019 2.037 30.3622 2283.9041 F8 NA 0.303622
## 584 -0.014 2.040 30.2000 1820.0200 F8 NA 0.302000
## 585 -0.010 2.039 30.5217 1922.0161 F8 NA 0.305217
## 586 -0.010 2.039 30.7000 1978.5601 F8 NA 0.307000
## 587 -0.012 2.039 31.3073 2853.9758 F8 NA 0.313073
## 588 -0.014 2.037 31.7000 3420.0000 F8 NA 0.317000
## 589 -0.016 2.035 31.0256 2846.9758 F8 NA 0.310256
## 590 -0.012 2.037 30.7000 2570.3201 F8 NA 0.307000
## 591 -0.003 2.043 30.5073 2393.9656 F8 NA 0.305073
## 592 0.002 2.051 30.4000 2295.7800 F8 NA 0.304000
## 593 0.008 2.068 31.1410 2918.3340 F8 NA 0.311410
## 594 0.010 2.100 31.5000 3220.0000 F8 NA 0.315000
## 595 -0.002 2.126 30.1588 2573.2031 F8 NA 0.301588
## 596 -0.017 2.122 29.6000 2303.7000 F8 NA 0.296000
## 597 -0.016 2.096 29.9528 2736.5945 F8 NA 0.299528
## 598 -0.012 2.074 30.2000 3040.0000 F8 NA 0.302000
## 599 -0.017 2.060 31.0981 3988.5752 F8 NA 0.310981
## 600 -0.019 2.050 31.8000 4730.0000 F8 NA 0.318000
## 601 -0.008 2.041 33.2112 3795.9231 F8 NA 0.332112
## 602 0.004 2.033 33.9000 3340.0000 F8 NA 0.339000
## 603 0.007 2.023 31.6376 2749.5947 F8 NA 0.316376
## 604 0.002 2.015 30.8000 2531.0000 F8 NA 0.308000
## 605 -0.006 2.012 31.1000 2348.8201 F8 NA 0.311000
## 606 -0.012 2.013 30.8607 2895.5957 F8 NA 0.308607
## 607 -0.013 2.015 30.5000 3720.0000 F8 NA 0.305000
## 608 -0.012 2.017 31.3120 3561.8772 F8 NA 0.313120
## 609 -0.006 2.019 32.4000 3350.0000 F8 NA 0.324000
## 610 -0.002 2.018 32.7522 3459.5876 F8 NA 0.327522
## 611 -0.002 2.015 33.3000 3630.0000 F8 NA 0.333000
## 612 -0.002 2.015 32.5681 3526.3140 F8 NA 0.325681
## 613 -0.001 2.018 32.1000 3460.0000 F8 NA 0.321000
## 614 -0.003 2.022 32.2147 2262.0811 F8 NA 0.322147
## 615 -0.007 2.026 32.3000 1371.3700 F8 NA 0.323000
## 616 -0.008 2.027 30.4321 1591.2185 F8 NA 0.304321
## 617 -0.007 2.025 29.2000 1736.2400 F8 NA 0.292000
## 618 -0.010 2.022 32.7000 1828.3900 F8 NA 0.327000
## 619 -0.013 2.019 32.7000 1952.0089 F8 NA 0.327000
## 620 -0.013 2.016 32.7000 2091.1111 F8 NA 0.327000
## 621 -0.011 2.015 32.7000 2183.5400 F8 NA 0.327000
## 622 -0.012 2.017 32.4000 2331.9900 F8 NA 0.324000
## 623 -0.011 2.023 31.0435 1619.7656 F8 NA 0.310435
## 624 -0.006 2.034 29.5000 809.4100 F8 NA 0.295000
## 625 -0.002 2.049 28.7544 603.8804 F8 NA 0.287544
## 626 -0.001 2.065 28.2285 458.8995 F8 NA 0.282285
## 627 -0.001 2.084 27.9000 368.3500 F9 NA 0.279000
## 628 -0.006 2.103 27.8367 383.8092 F9 NA 0.278367
## 629 -0.012 2.120 27.8000 392.7800 F9 NA 0.278000
## 630 -0.014 2.127 27.0259 369.4849 F9 NA 0.270259
## 631 -0.009 2.122 26.4000 350.6500 F9 NA 0.264000
## 632 -0.005 2.112 31.7000 1862.8700 F9 NA 0.317000
## 633 -0.006 2.107 29.3212 1181.2034 F9 NA 0.293212
## 634 -0.007 2.106 26.1000 258.1300 F9 NA 0.261000
## 635 -0.002 2.105 27.6000 465.0500 F9 NA 0.276000
## 636 0.004 2.105 27.7100 371.8761 F9 NA 0.277100
## 637 -0.005 2.112 27.7507 287.3767 F9 NA 0.277507
## 638 -0.003 2.118 27.7037 279.4883 F9 NA 0.277037
## 639 0.001 2.122 27.6566 271.5998 F9 NA 0.276566
## 640 -0.002 2.126 27.6096 263.7113 F9 NA 0.276096
## 641 -0.005 2.136 27.5625 255.8228 F9 NA 0.275625
## 642 -0.002 2.151 27.5155 247.9343 F9 NA 0.275155
## 643 0.003 2.160 27.4684 240.0458 F9 NA 0.274684
## 644 0.007 2.158 27.4000 228.5700 F9 NA 0.274000
## 645 0.006 2.148 26.5112 242.9852 F9 NA 0.265112
## 646 0.003 2.137 24.1000 282.0900 F9 NA 0.241000
## 647 0.004 2.130 24.3573 332.4404 F9 NA 0.243573
## 648 0.007 2.131 25.0000 458.2000 F9 NA 0.250000
## 649 0.005 2.138 24.9655 437.7937 F9 NA 0.249655
## 650 -0.001 2.147 24.9000 399.1000 F9 NA 0.249000
## 651 -0.003 2.152 25.0481 431.1000 F9 NA 0.250481
## 652 0.001 2.155 25.3000 485.5200 F9 NA 0.253000
## 653 0.002 2.156 25.2234 459.3311 F9 NA 0.252234
## 654 -0.005 2.155 25.1000 417.1300 F9 NA 0.251000
## 655 -0.009 2.151 25.2124 480.6394 F9 NA 0.252124
## 656 -0.006 2.146 25.3921 582.1041 F9 NA 0.253921
## 657 -0.004 2.140 25.5000 643.0700 F9 NA 0.255000
## 658 -0.004 2.134 26.0000 499.3700 F9 NA 0.260000
## 659 -0.004 2.131 25.9482 447.7827 F9 NA 0.259482
## 660 -0.005 2.129 25.8583 358.4117 F9 NA 0.258583
## 661 -0.006 2.126 25.8000 300.3600 F9 NA 0.258000
## 662 -0.008 2.122 25.5999 240.2611 F9 NA 0.255999
## 663 -0.011 2.122 25.5000 210.2700 F9 NA 0.255000
## 664 -0.012 2.127 24.5000 216.6000 F9 NA 0.245000
## 665 -0.012 2.131 24.8623 257.7916 F9 NA 0.248623
## 666 -0.014 2.134 25.5808 339.4923 F9 NA 0.255808
## 667 -0.015 2.136 26.1000 398.5300 F9 NA 0.261000
## 668 -0.014 2.138 26.6048 669.3860 F9 NA 0.266048
## 669 -0.014 2.139 26.9000 827.7700 F9 NA 0.269000
## 670 -0.015 2.132 27.2095 896.8858 F9 NA 0.272095
## 671 -0.012 2.122 27.4000 939.4300 F9 NA 0.274000
## 672 -0.006 2.117 26.8537 780.4501 F9 NA 0.268537
## 673 -0.004 2.118 26.5000 677.5000 F9 NA 0.265000
## 674 -0.008 2.118 27.0408 710.9836 F9 NA 0.270408
## 675 -0.009 2.114 27.5000 739.4100 F9 NA 0.275000
## 676 -0.004 2.106 27.1781 729.7252 F9 NA 0.271781
## 677 -0.002 2.094 26.9000 721.3600 F9 NA 0.269000
## 678 -0.003 2.084 26.8429 917.3568 F9 NA 0.268429
## 679 -0.005 2.085 26.8000 1064.6899 F9 NA 0.268000
## 680 -0.011 2.093 26.6323 963.2323 F9 NA 0.266323
## 681 -0.017 2.101 26.5000 883.1400 F9 NA 0.265000
## 682 -0.013 2.103 26.6823 999.1555 F9 NA 0.266823
## 683 -0.003 2.101 26.8000 1074.0900 F9 NA 0.268000
## 684 -0.004 2.095 27.1462 1209.9685 F9 NA 0.271462
## 685 -0.010 2.088 27.4000 1309.5500 F9 NA 0.274000
## 686 -0.010 2.083 27.1677 1053.1267 F9 NA 0.271677
## 687 -0.007 2.082 27.0000 868.0800 F9 NA 0.270000
## 688 -0.008 2.086 27.4886 865.2035 F9 NA 0.274886
## 689 -0.007 2.093 27.8000 863.3700 F9 NA 0.278000
## 690 -0.004 2.099 28.8644 1137.1615 F9 NA 0.288644
## 691 -0.004 2.103 29.4000 1274.9500 F9 NA 0.294000
## 692 -0.002 2.107 29.3019 1259.5554 F9 NA 0.293019
## 693 0.002 2.112 29.2313 1248.4808 F9 NA 0.292313
## 694 0.003 2.115 29.1608 1237.4061 F9 NA 0.291608
## 695 -0.001 2.115 29.1000 1227.8700 F9 NA 0.291000
## 696 -0.007 2.111 28.7308 1102.0452 F9 NA 0.287308
## 697 -0.010 2.103 28.4066 991.5684 F9 NA 0.284066
## 698 -0.010 2.096 28.0824 881.0916 F9 NA 0.280824
## 699 -0.009 2.091 27.7583 770.6147 F9 NA 0.277583
## 700 -0.004 2.090 27.4341 660.1379 F9 NA 0.274341
## 701 -0.001 2.094 27.0000 512.2100 F9 NA 0.270000
## 702 -0.003 2.101 27.0891 537.4426 F9 NA 0.270891
## 703 -0.008 2.108 27.2238 575.6158 F9 NA 0.272238
## 704 -0.009 2.116 27.3585 613.7889 F9 NA 0.273585
## 705 -0.005 2.123 27.4932 651.9620 F9 NA 0.274932
## 706 0.002 2.124 27.6279 690.1351 F9 NA 0.276279
## 707 0.007 2.121 27.7627 728.3082 F9 NA 0.277627
## 708 0.007 2.121 27.9000 767.2200 F9 NA 0.279000
## 709 0.003 2.127 27.5274 729.5110 F9 NA 0.275274
## 710 -0.005 2.133 27.1474 691.0581 F9 NA 0.271474
## 711 -0.014 2.134 26.7674 652.6051 F9 NA 0.267674
## 712 -0.013 2.128 26.3874 614.1521 F9 NA 0.263874
## 713 -0.009 2.120 25.9000 564.8300 F9 NA 0.259000
## 714 -0.008 2.112 26.0536 609.7765 F9 NA 0.260536
## 715 -0.007 2.107 26.2676 672.4337 F9 NA 0.262676
## 716 -0.003 2.104 26.4817 735.0908 F9 NA 0.264817
## 717 0.002 2.105 26.6957 797.7479 F9 NA 0.266957
## 718 0.004 2.112 26.9098 860.4050 F9 NA 0.269098
## 719 0.004 2.118 27.2000 945.3500 F9 NA 0.272000
## 720 -0.004 2.118 27.3354 770.6907 F9 NA 0.273354
## 721 -0.004 2.115 27.4177 664.4689 F9 NA 0.274177
## 722 -0.001 2.113 27.5000 558.2472 F9 NA 0.275000
## 723 0.003 2.116 27.5824 452.0254 F9 NA 0.275824
## 724 0.003 2.119 27.7000 300.2600 F9 NA 0.277000
## 725 -0.003 2.119 27.6248 321.5066 F9 NA 0.276248
## 726 -0.014 2.115 27.4930 358.7004 F9 NA 0.274930
## 727 -0.022 2.108 27.3613 395.8943 F9 NA 0.273613
## 728 -0.024 2.101 27.2296 433.0881 F9 NA 0.272296
## 729 -0.019 2.097 27.0978 470.2819 F9 NA 0.270978
## 730 -0.007 2.098 26.9661 507.4758 F9 NA 0.269661
## 731 0.003 2.102 26.9000 526.1400 F9 NA 0.269000
## 732 0.002 2.106 27.4181 893.3821 F9 NA 0.274181
## 733 -0.005 2.110 27.7638 1138.5061 F9 NA 0.277638
## 734 -0.008 2.114 28.1096 1383.6300 F9 NA 0.281096
## 735 -0.002 2.116 28.4554 1628.7540 F9 NA 0.284554
## 736 0.003 2.111 28.8012 1873.8779 F9 NA 0.288012
## 737 0.002 2.097 29.0000 2014.7900 F9 NA 0.290000
## 738 -0.001 2.085 28.5072 1743.1687 F9 NA 0.285072
## 739 -0.002 2.091 28.1614 1552.5758 F9 NA 0.281614
## 740 -0.016 2.124 27.8156 1361.9829 F9 NA 0.278156
## 741 -0.051 2.161 27.4698 1171.3900 F9 NA 0.274698
## 742 -0.067 2.167 27.1240 980.7972 F9 NA 0.271240
## 743 -0.040 2.136 26.9000 857.3100 F9 NA 0.269000
## 744 -0.007 2.108 27.4343 1089.8239 F9 NA 0.274343
## 745 0.002 2.101 27.8295 1261.7902 F9 NA 0.278295
## 746 0.002 2.106 28.2247 1433.7565 F9 NA 0.282247
## 747 0.005 2.121 28.6199 1605.7228 F9 NA 0.286199
## 748 0.006 2.141 29.0151 1777.6891 F9 NA 0.290151
## 749 -0.007 2.172 28.9249 1708.2007 F9 NA 0.289249
## 750 -0.012 2.171 28.6315 1556.9391 F9 NA 0.286315
## 751 -0.014 2.157 28.3382 1405.6776 F9 NA 0.283382
## 752 -0.011 2.140 28.0449 1254.4161 F9 NA 0.280449
## 753 -0.007 2.130 27.7516 1103.1545 F9 NA 0.277516
## 754 -0.006 2.128 27.4000 921.8100 F9 NA 0.274000
## 755 -0.008 2.130 27.1447 910.1433 F9 NA 0.271447
## 756 -0.008 2.134 26.8260 895.5803 F9 NA 0.268260
## 757 -0.005 2.141 26.5073 881.0173 F9 NA 0.265073
## 758 -0.002 2.147 26.1886 866.4542 F9 NA 0.261886
## 759 -0.002 2.148 25.8699 851.8912 F9 NA 0.258699
## 760 -0.003 2.146 25.4000 830.4200 F9 NA 0.254000
## 761 -0.007 2.140 25.2557 817.8306 F9 NA 0.252557
## 762 -0.012 2.128 24.9813 793.8796 F9 NA 0.249813
## 763 -0.014 2.113 24.7069 769.9286 F9 NA 0.247069
## 764 -0.014 2.099 24.4324 745.9776 F9 NA 0.244324
## 765 -0.013 2.091 24.1580 722.0266 F9 NA 0.241580
## 766 -0.009 2.091 23.9000 699.5100 F9 NA 0.239000
## 767 -0.004 2.095 24.2038 831.6595 F9 NA 0.242038
## 768 -0.001 2.099 24.4904 956.3419 F9 NA 0.244904
## 769 -0.001 2.111 25.0637 1205.7067 F9 NA 0.250637
## 770 -0.003 2.116 25.3503 1330.3890 F9 NA 0.253503
## 771 -0.004 2.118 25.6000 1439.0200 F9 NA 0.256000
## 772 -0.003 2.120 26.1148 1876.8239 F9 NA 0.261148
## 773 -0.003 2.126 26.5710 2264.6938 F9 NA 0.265710
## 774 -0.001 2.139 27.0271 2652.5637 F9 NA 0.270271
## 775 -0.001 2.154 27.4832 3040.4338 F9 NA 0.274832
## 776 -0.001 2.164 27.9393 3428.3037 F9 NA 0.279393
## 777 0.004 2.160 28.2000 3650.0000 F9 NA 0.282000
## 778 0.006 2.148 26.5962 2797.1609 F9 NA 0.265962
## 779 -0.001 2.140 25.4735 2200.1130 F9 NA 0.254735
## 780 -0.005 2.145 24.3507 1603.0649 F9 NA 0.243507
## 781 0.003 2.168 23.2280 1006.0170 F9 NA 0.232280
## 782 0.009 2.204 21.8000 246.6400 F9 NA 0.218000
## 783 -0.005 2.229 22.3628 298.5033 F9 NA 0.223628
## 784 -0.022 2.222 23.1358 369.7330 F9 NA 0.231358
## 785 -0.017 2.193 23.9088 440.9626 F9 NA 0.239088
## 786 -0.003 2.166 24.6818 512.1923 F9 NA 0.246818
## 787 0.002 2.149 25.4548 583.4219 F9 NA 0.254548
## 788 0.001 2.136 26.5000 679.7400 F9 NA 0.265000
## 789 0.003 2.127 26.4295 712.3636 F9 NA 0.264295
## 790 0.008 2.124 26.3206 762.7256 F9 NA 0.263206
## 791 0.007 2.125 26.2117 813.0876 F9 NA 0.262117
## 792 -0.004 2.124 26.1028 863.4496 F9 NA 0.261028
## 793 -0.012 2.116 25.9939 913.8117 F9 NA 0.259939
## 794 -0.007 2.104 25.9000 957.2500 F9 NA 0.259000
## 795 0.001 2.089 26.4587 1528.5027 F9 NA 0.264587
## 796 0.004 2.076 26.9499 2030.7120 F9 NA 0.269499
## 797 0.004 2.069 27.4411 2532.9214 F9 NA 0.274411
## 798 0.002 2.072 27.9323 3035.1306 F9 NA 0.279323
## 799 -0.003 2.099 28.7000 3820.0000 F5 NA 0.287000
## 800 -0.005 2.108 29.2799 5020.0947 F5 NA 0.292799
## 801 -0.002 2.113 29.6834 5855.1367 F5 NA 0.296834
## 802 0.002 2.119 30.0869 6690.1787 F5 NA 0.300869
## 803 0.003 2.130 30.4903 7525.2207 F5 NA 0.304903
## 804 -0.010 2.148 30.6122 9458.1729 F5 NA 0.306122
## 805 -0.019 2.141 30.0859 10649.9580 F5 NA 0.300859
## 806 -0.017 2.127 29.5596 11841.7432 F5 NA 0.295596
## 807 -0.009 2.117 29.0333 13033.5283 F5 NA 0.290333
## 808 -0.005 2.110 28.5071 14225.3135 F5 NA 0.285071
## 809 -0.001 2.102 27.9000 15600.0000 F5 NA 0.279000
## 810 0.005 2.094 27.7563 13544.9785 F5 NA 0.277563
## 811 0.006 2.091 27.5865 11117.4023 F5 NA 0.275865
## 812 0.001 2.095 27.4167 8689.8252 F5 NA 0.274167
## 813 -0.002 2.105 27.2470 6262.2485 F5 NA 0.272470
## 814 0.003 2.147 26.9000 1300.7900 F5 NA 0.269000
## 815 -0.002 2.162 25.7547 1249.7059 F5 NA 0.257547
## 816 -0.008 2.158 24.5569 1196.2823 F5 NA 0.245569
## 817 -0.006 2.136 23.3592 1142.8588 F5 NA 0.233592
## 818 -0.002 2.115 22.1614 1089.4352 F5 NA 0.221614
## 819 -0.003 2.109 20.9637 1036.0116 F5 NA 0.209637data=data[, sapply(data, function(x) length(unique(x))>1)]
data$Facies=as.factor(data$Facies)
library(caret)## Loading required package: ggplot2## Loading required package: latticeSet Working Directory: The working directory is set to “C:/Users/muqta/Desktop/rdata” where the dataset is stored. This allows access to the karpur.csv file. Read Data: The CSV file karpur.csv is read into the data dataframe. Remove Constant Columns: Any column in the dataset that has only one unique value is removed using sapply(data, function(x) length(unique(x)) > 1). This step is to eliminate columns that do not provide useful variation for modeling. Convert Facies to Factor: The Facies variable is converted to a factor (categorical variable) since it’s likely categorical. Load caret Package: The caret package is loaded, which provides functions like RMSE to calculate performance metrics for regression models. ##Step 2: Build Model 1 - Linear Regression Without Facies
model_1<- lm(k.core~ .-Facies,data=data)
summary(model_1)##
## Call:
## lm(formula = k.core ~ . - Facies, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5549.5 -755.5 -178.1 578.0 11260.8
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60762.728 16605.360 3.659 0.000269 ***
## depth -7.398 1.446 -5.115 3.92e-07 ***
## caliper -3955.952 1055.105 -3.749 0.000190 ***
## ind.deep -14.183 2.345 -6.048 2.24e-09 ***
## ind.med 17.300 2.509 6.896 1.08e-11 ***
## gamma -77.487 5.475 -14.153 < 2e-16 ***
## phi.N -1784.704 1301.772 -1.371 0.170763
## R.deep -26.007 6.974 -3.729 0.000206 ***
## R.med 63.525 9.841 6.455 1.86e-10 ***
## SP -8.784 3.460 -2.539 0.011313 *
## density.corr -523.060 5358.876 -0.098 0.922269
## density 8011.106 1120.554 7.149 1.96e-12 ***
## phi.core 183.203 23.802 7.697 4.07e-14 ***
## phi.core.frac NA NA NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1442 on 806 degrees of freedom
## Multiple R-squared: 0.5903, Adjusted R-squared: 0.5842
## F-statistic: 96.77 on 12 and 806 DF, p-value: < 2.2e-16k.predicted_1 <-predict(model_1,data=data)
plot(k.predicted_1,data$k.core)
Model Creation: model_1 is a linear regression model where k.core is
predicted using all other variables in the dataset, excluding Facies.
Summary: The summary(model_1) command gives detailed results of the
model, including coefficients and p-values for each variable.
Predictions: The predict() function generates predicted values
(k.predicted_1) using the model. Plot: The predicted values are plotted
against the actual k.core values to visually assess the model’s
performance.
##Step 3: Calculate RMSE for Model 1
rmse_1<- RMSE(k.predicted_1,data$k.core )
rmse_1## [1] 1430.118RMSE Calculation: The RMSE (Root Mean Squared Error) between the predicted and actual values is calculated. RMSE is a common evaluation metric for regression models that measures how far the predicted values are from the actual values.
##Step 4: Build Model 2 - Backward Stepwise Regression on Model 1
model_2<-step(model_1 , direction = "backward")## Start: AIC=11926.91
## k.core ~ (depth + caliper + ind.deep + ind.med + gamma + phi.N +
## R.deep + R.med + SP + density.corr + density + phi.core +
## Facies + phi.core.frac) - Facies
##
##
## Step: AIC=11926.91
## k.core ~ depth + caliper + ind.deep + ind.med + gamma + phi.N +
## R.deep + R.med + SP + density.corr + density + phi.core
##
## Df Sum of Sq RSS AIC
## - density.corr 1 19799 1675068713 11925
## - phi.N 1 3906205 1678955118 11927
## <none> 1675048914 11927
## - SP 1 13394190 1688443104 11931
## - R.deep 1 28897686 1703946599 11939
## - caliper 1 29214826 1704263740 11939
## - depth 1 54372650 1729421563 11951
## - ind.deep 1 76022788 1751071701 11961
## - R.med 1 86603706 1761652619 11966
## - ind.med 1 98823752 1773872666 11972
## - density 1 106221406 1781270319 11975
## - phi.core 1 123125117 1798174031 11983
## - gamma 1 416312526 2091361440 12107
##
## Step: AIC=11924.92
## k.core ~ depth + caliper + ind.deep + ind.med + gamma + phi.N +
## R.deep + R.med + SP + density + phi.core
##
## Df Sum of Sq RSS AIC
## <none> 1675068713 11925
## - phi.N 1 4564880 1679633593 11925
## - SP 1 13491079 1688559792 11930
## - R.deep 1 28896144 1703964857 11937
## - caliper 1 29253869 1704322581 11937
## - depth 1 54825159 1729893872 11949
## - ind.deep 1 77573926 1752642639 11960
## - R.med 1 86772220 1761840933 11964
## - ind.med 1 100740701 1775809413 11971
## - density 1 114209586 1789278299 11977
## - phi.core 1 124694278 1799762991 11982
## - gamma 1 417015194 2092083907 12105summary(model_2)##
## Call:
## lm(formula = k.core ~ depth + caliper + ind.deep + ind.med +
## gamma + phi.N + R.deep + R.med + SP + density + phi.core,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5545.3 -753.4 -177.1 576.8 11260.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60910.619 16525.937 3.686 0.000243 ***
## depth -7.409 1.442 -5.139 3.46e-07 ***
## caliper -3957.892 1054.270 -3.754 0.000186 ***
## ind.deep -14.146 2.314 -6.113 1.52e-09 ***
## ind.med 17.263 2.478 6.967 6.74e-12 ***
## gamma -77.461 5.465 -14.174 < 2e-16 ***
## phi.N -1825.771 1231.150 -1.483 0.138470
## R.deep -25.972 6.961 -3.731 0.000204 ***
## R.med 63.466 9.816 6.466 1.75e-10 ***
## SP -8.803 3.453 -2.549 0.010974 *
## density 7980.761 1075.902 7.418 3.02e-13 ***
## phi.core 183.436 23.667 7.751 2.75e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1441 on 807 degrees of freedom
## Multiple R-squared: 0.5903, Adjusted R-squared: 0.5847
## F-statistic: 105.7 on 11 and 807 DF, p-value: < 2.2e-16k.predicted_2 <-predict(model_2,data=data)
plot(k.predicted_2,data$k.core)
Backward Stepwise Selection: The step() function performs backward
stepwise regression. It starts with all variables in the model and
removes the least significant predictors (based on p-value) until only
the most important predictors remain. Predictions and Plot: Predictions
are made with the simplified model model_2, and these predictions are
compared to actual values using a scatter plot.
##Step 5: Calculate RMSE for Model 2
rmse_2<- RMSE(k.predicted_2,data$k.core )
rmse_2## [1] 1430.126RMSE Calculation: The RMSE for model_2 is computed to evaluate its predictive performance.
##Step 6: Build Model 3 - Linear Regression with All Predictors
model_3<- lm(k.core~ .,data=data)
summary(model_3)##
## Call:
## lm(formula = k.core ~ ., data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5585.6 -568.9 49.2 476.5 8928.4
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.783e+04 1.760e+04 -3.853 0.000126 ***
## depth 8.544e+00 1.785e+00 4.786 2.02e-06 ***
## caliper 1.413e+03 1.019e+03 1.387 0.165789
## ind.deep -2.418e-01 2.354e+00 -0.103 0.918220
## ind.med 1.224e+00 2.585e+00 0.473 0.636062
## gamma -4.583e+01 6.010e+00 -7.626 6.88e-14 ***
## phi.N -2.010e+03 1.476e+03 -1.362 0.173540
## R.deep -2.344e+01 6.288e+00 -3.727 0.000207 ***
## R.med 5.643e+01 9.065e+00 6.225 7.76e-10 ***
## SP -7.125e+00 3.145e+00 -2.266 0.023736 *
## density.corr -2.567e+03 4.809e+03 -0.534 0.593602
## density 2.319e+03 1.173e+03 1.976 0.048458 *
## phi.core 1.921e+02 2.282e+01 8.418 < 2e-16 ***
## FaciesF10 8.921e+02 3.590e+02 2.485 0.013157 *
## FaciesF2 9.243e+02 5.818e+02 1.589 0.112514
## FaciesF3 4.393e+02 3.344e+02 1.313 0.189394
## FaciesF5 7.411e+02 3.428e+02 2.162 0.030908 *
## FaciesF7 -4.152e+01 5.742e+02 -0.072 0.942377
## FaciesF8 -1.179e+03 3.927e+02 -3.002 0.002770 **
## FaciesF9 -2.969e+03 4.298e+02 -6.908 1.00e-11 ***
## phi.core.frac NA NA NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1262 on 799 degrees of freedom
## Multiple R-squared: 0.6889, Adjusted R-squared: 0.6815
## F-statistic: 93.12 on 19 and 799 DF, p-value: < 2.2e-16k.predicted_3 <-predict(model_3,data=data)
plot(k.predicted_3,data$k.core)
Model Creation: model_3 is a linear regression model using all
predictors in the dataset to predict k.core. Summary: The summary of
model_3 provides detailed results, including statistical information
about the predictors. Predictions and Plot: Predictions are made using
model_3 and visualized against actual k.core values.
##Step 7: Calculate RMSE for Model 3
rmse_3<- RMSE(k.predicted_3,data$k.core )
rmse_3## [1] 1246.201RMSE Calculation: The RMSE for model_3 is calculated to evaluate its predictive performance.
##Step 8: Build Model 4 - Backward Stepwise Regression on Model 3
model_4<-step(model_3 , direction = "backward")## Start: AIC=11715.43
## k.core ~ depth + caliper + ind.deep + ind.med + gamma + phi.N +
## R.deep + R.med + SP + density.corr + density + phi.core +
## Facies + phi.core.frac
##
##
## Step: AIC=11715.43
## k.core ~ depth + caliper + ind.deep + ind.med + gamma + phi.N +
## R.deep + R.med + SP + density.corr + density + phi.core +
## Facies
##
## Df Sum of Sq RSS AIC
## - ind.deep 1 16793 1271937992 11713
## - ind.med 1 356746 1272277945 11714
## - density.corr 1 453661 1272374861 11714
## - phi.N 1 2953609 1274874809 11715
## - caliper 1 3063007 1274984206 11715
## <none> 1271921199 11715
## - density 1 6217927 1278139127 11717
## - SP 1 8171834 1280093033 11719
## - R.deep 1 22117394 1294038593 11728
## - depth 1 36466976 1308388176 11737
## - R.med 1 61690461 1333611660 11752
## - gamma 1 92579723 1364500923 11771
## - phi.core 1 112793101 1384714301 11783
## - Facies 7 403127714 1675048914 11927
##
## Step: AIC=11713.44
## k.core ~ depth + caliper + ind.med + gamma + phi.N + R.deep +
## R.med + SP + density.corr + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - density.corr 1 437546 1272375538 11712
## - phi.N 1 2938766 1274876758 11713
## - caliper 1 3074396 1275012389 11713
## <none> 1271937992 11713
## - density 1 6228928 1278166920 11715
## - ind.med 1 6905855 1278843848 11716
## - SP 1 8191802 1280129794 11717
## - R.deep 1 22125695 1294063687 11726
## - depth 1 39139470 1311077462 11736
## - R.med 1 61773953 1333711946 11750
## - gamma 1 92865220 1364803212 11769
## - phi.core 1 112960440 1384898432 11781
## - Facies 7 479133709 1751071701 11961
##
## Step: AIC=11711.72
## k.core ~ depth + caliper + ind.med + gamma + phi.N + R.deep +
## R.med + SP + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - caliper 1 2980713 1275356252 11712
## <none> 1272375538 11712
## - phi.N 1 3279032 1275654571 11712
## - density 1 5792837 1278168375 11713
## - ind.med 1 6813959 1279189497 11714
## - SP 1 8391302 1280766840 11715
## - R.deep 1 22009402 1294384940 11724
## - depth 1 38705776 1311081314 11734
## - R.med 1 61436819 1333812357 11748
## - gamma 1 93974329 1366349868 11768
## - phi.core 1 115336515 1387712053 11781
## - Facies 7 480267100 1752642639 11960
##
## Step: AIC=11711.64
## k.core ~ depth + ind.med + gamma + phi.N + R.deep + R.med + SP +
## density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - phi.N 1 2534906 1277891157 11711
## <none> 1275356252 11712
## - density 1 7270311 1282626562 11714
## - SP 1 8733336 1284089587 11715
## - ind.med 1 12924050 1288280301 11718
## - R.deep 1 22449117 1297805369 11724
## - depth 1 51507476 1326863728 11742
## - R.med 1 60137982 1335494234 11747
## - phi.core 1 112564835 1387921086 11779
## - gamma 1 141535555 1416891807 11796
## - Facies 7 520094756 1795451008 11978
##
## Step: AIC=11711.26
## k.core ~ depth + ind.med + gamma + R.deep + R.med + SP + density +
## phi.core + Facies
##
## Df Sum of Sq RSS AIC
## <none> 1277891157 11711
## - density 1 5155969 1283047127 11713
## - SP 1 8515796 1286406953 11715
## - ind.med 1 10944937 1288836095 11716
## - R.deep 1 23273312 1301164469 11724
## - depth 1 49725248 1327616405 11740
## - R.med 1 59454645 1337345802 11746
## - phi.core 1 110154394 1388045551 11777
## - gamma 1 219059092 1496950249 11839
## - Facies 7 526383446 1804274603 11980summary(model_4)##
## Call:
## lm(formula = k.core ~ depth + ind.med + gamma + R.deep + R.med +
## SP + density + phi.core + Facies, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5608.3 -567.8 35.9 500.7 8989.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.322e+04 6.625e+03 -6.523 1.22e-10 ***
## depth 6.648e+00 1.189e+00 5.590 3.11e-08 ***
## ind.med 1.078e+00 4.111e-01 2.623 0.008894 **
## gamma -5.324e+01 4.537e+00 -11.733 < 2e-16 ***
## R.deep -2.395e+01 6.264e+00 -3.824 0.000141 ***
## R.med 5.515e+01 9.022e+00 6.112 1.53e-09 ***
## SP -7.214e+00 3.118e+00 -2.313 0.020960 *
## density 1.880e+03 1.044e+03 1.800 0.072240 .
## phi.core 1.817e+02 2.184e+01 8.320 3.77e-16 ***
## FaciesF10 8.266e+02 3.533e+02 2.340 0.019553 *
## FaciesF2 7.035e+02 5.567e+02 1.264 0.206697
## FaciesF3 4.100e+02 3.228e+02 1.270 0.204443
## FaciesF5 5.913e+02 3.211e+02 1.841 0.065924 .
## FaciesF7 -3.159e+02 5.402e+02 -0.585 0.558866
## FaciesF8 -1.455e+03 3.122e+02 -4.661 3.69e-06 ***
## FaciesF9 -3.017e+03 3.764e+02 -8.017 3.82e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1262 on 803 degrees of freedom
## Multiple R-squared: 0.6874, Adjusted R-squared: 0.6816
## F-statistic: 117.7 on 15 and 803 DF, p-value: < 2.2e-16k.predicted_4 <-predict(model_4,data=data)
plot(k.predicted_4,data$k.core)
Backward Stepwise Selection: Again, backward stepwise selection is
applied to model_3 to create model_4, simplifying the model by removing
less important predictors. Predictions and Plot: Predictions are made
using model_4 and compared to the actual values of k.core.
##Step 9: Calculate RMSE for Model 4
rmse_4<- RMSE(k.predicted_4,data$k.core )
rmse_4## [1] 1249.122RMSE Calculation: The RMSE for model_4 is computed to assess its performance
##Step 10: Log Transformation of k.core
data$log10_k.core<-log10(data$k.core)
model_5<- lm(log10_k.core~.-k.core,data=data)
summary(model_5)##
## Call:
## lm(formula = log10_k.core ~ . - k.core, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5804 -0.1138 0.0322 0.1529 0.7384
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.3461877 4.6532000 -0.504 0.61425
## depth 0.0007425 0.0004718 1.574 0.11596
## caliper -0.4605945 0.2693103 -1.710 0.08760 .
## ind.deep -0.0007951 0.0006222 -1.278 0.20168
## ind.med 0.0007137 0.0006833 1.044 0.29659
## gamma -0.0091269 0.0015885 -5.746 1.30e-08 ***
## phi.N -1.7628155 0.3901024 -4.519 7.16e-06 ***
## R.deep -0.0025878 0.0016620 -1.557 0.11987
## R.med 0.0044073 0.0023960 1.839 0.06622 .
## SP -0.0016935 0.0008312 -2.037 0.04194 *
## density.corr 1.4462633 1.2712045 1.138 0.25558
## density 1.6148374 0.3100921 5.208 2.44e-07 ***
## phi.core 0.0948634 0.0060329 15.724 < 2e-16 ***
## FaciesF10 0.0786460 0.0948909 0.829 0.40746
## FaciesF2 -0.0184334 0.1537793 -0.120 0.90462
## FaciesF3 -0.0307548 0.0883957 -0.348 0.72799
## FaciesF5 0.1094193 0.0906034 1.208 0.22753
## FaciesF7 0.2811620 0.1517797 1.852 0.06433 .
## FaciesF8 -0.0976234 0.1038054 -0.940 0.34727
## FaciesF9 -0.3562116 0.1135966 -3.136 0.00178 **
## phi.core.frac NA NA NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3335 on 799 degrees of freedom
## Multiple R-squared: 0.6806, Adjusted R-squared: 0.673
## F-statistic: 89.6 on 19 and 799 DF, p-value: < 2.2e-16log_k.predicted_5 <-predict(model_5,data=data)
k.predicted_5<-10^log_k.predicted_5
plot(k.predicted_5,data$k.core)
Log Transformation: A new column log10_k.core is created by applying a
logarithmic transformation (log10) to k.core. This can help stabilize
variance if k.core has a skewed distribution. Model Creation: A linear
regression model (model_5) is created to predict the log-transformed
k.core. Predictions: Predictions are made using the log-transformed
model, then inverse-transformed by raising 10 to the power of the
predicted values (10^log_k.predicted_5) to get back to the original
scale of k.core. Plot: The predicted values (k.predicted_5) are plotted
against the actual values (data$k.core).
##Step 11: Calculate RMSE for Model 5
rmse_5<- RMSE(k.predicted_5,data$k.core )
rmse_5## [1] 1333.017RMSE Calculation: The RMSE for model_5 is calculated, comparing the log-transformed predictions back to the original k.core values.
##Step 12: Backward Stepwise Regression on Log-Transformed Model
model_6<-step(model_5, direction = "backward")## Start: AIC=-1779.02
## log10_k.core ~ (depth + caliper + ind.deep + ind.med + gamma +
## phi.N + R.deep + R.med + SP + density.corr + density + phi.core +
## k.core + Facies + phi.core.frac) - k.core
##
##
## Step: AIC=-1779.02
## log10_k.core ~ depth + caliper + ind.deep + ind.med + gamma +
## phi.N + R.deep + R.med + SP + density.corr + density + phi.core +
## Facies
##
## Df Sum of Sq RSS AIC
## - ind.med 1 0.1213 88.981 -1779.9
## - density.corr 1 0.1440 89.004 -1779.7
## - ind.deep 1 0.1816 89.042 -1779.3
## <none> 88.860 -1779.0
## - R.deep 1 0.2696 89.130 -1778.5
## - depth 1 0.2754 89.135 -1778.5
## - caliper 1 0.3253 89.185 -1778.0
## - R.med 1 0.3763 89.236 -1777.6
## - SP 1 0.4617 89.322 -1776.8
## - phi.N 1 2.2710 91.131 -1760.3
## - density 1 3.0160 91.876 -1753.7
## - gamma 1 3.6713 92.531 -1747.9
## - Facies 7 7.0758 95.936 -1730.3
## - phi.core 1 27.4982 116.358 -1560.2
##
## Step: AIC=-1779.9
## log10_k.core ~ depth + caliper + ind.deep + gamma + phi.N + R.deep +
## R.med + SP + density.corr + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - density.corr 1 0.1931 89.174 -1780.1
## <none> 88.981 -1779.9
## - ind.deep 1 0.2179 89.199 -1779.9
## - R.deep 1 0.2447 89.226 -1779.7
## - caliper 1 0.2921 89.273 -1779.2
## - R.med 1 0.3397 89.321 -1778.8
## - SP 1 0.4101 89.391 -1778.1
## - depth 1 0.4622 89.444 -1777.7
## - phi.N 1 2.2035 91.185 -1761.9
## - density 1 3.0113 91.993 -1754.6
## - gamma 1 3.5761 92.557 -1749.6
## - Facies 7 9.1242 98.106 -1714.0
## - phi.core 1 27.4190 116.400 -1561.9
##
## Step: AIC=-1780.12
## log10_k.core ~ depth + caliper + ind.deep + gamma + phi.N + R.deep +
## R.med + SP + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - ind.deep 1 0.2180 89.392 -1780.1
## <none> 89.174 -1780.1
## - R.deep 1 0.2526 89.427 -1779.8
## - caliper 1 0.2676 89.442 -1779.7
## - R.med 1 0.3598 89.534 -1778.8
## - SP 1 0.3832 89.558 -1778.6
## - depth 1 0.5404 89.715 -1777.2
## - phi.N 1 2.0726 91.247 -1763.3
## - gamma 1 3.4838 92.658 -1750.7
## - density 1 3.6220 92.796 -1749.5
## - Facies 7 9.3567 98.531 -1712.4
## - phi.core 1 27.2273 116.402 -1563.9
##
## Step: AIC=-1780.12
## log10_k.core ~ depth + caliper + gamma + phi.N + R.deep + R.med +
## SP + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## <none> 89.392 -1780.1
## - R.deep 1 0.2869 89.679 -1779.5
## - depth 1 0.3332 89.726 -1779.1
## - SP 1 0.4296 89.822 -1778.2
## - R.med 1 0.5085 89.901 -1777.5
## - caliper 1 0.5746 89.967 -1776.9
## - phi.N 1 2.3337 91.726 -1761.0
## - gamma 1 3.8214 93.214 -1747.8
## - density 1 3.8626 93.255 -1747.5
## - Facies 7 9.2100 98.602 -1713.8
## - phi.core 1 27.0935 116.486 -1565.3summary(model_6)##
## Call:
## lm(formula = log10_k.core ~ depth + caliper + gamma + phi.N +
## R.deep + R.med + SP + density + phi.core + Facies, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.58182 -0.12001 0.03437 0.15230 0.70317
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.2671250 3.9316796 -0.322 0.74732
## depth 0.0006562 0.0003796 1.729 0.08420 .
## caliper -0.5608681 0.2470292 -2.270 0.02344 *
## gamma -0.0091497 0.0015626 -5.855 6.94e-09 ***
## phi.N -1.7463527 0.3816550 -4.576 5.50e-06 ***
## R.deep -0.0026554 0.0016551 -1.604 0.10903
## R.med 0.0049837 0.0023334 2.136 0.03300 *
## SP -0.0016140 0.0008221 -1.963 0.04996 *
## density 1.7602255 0.2990153 5.887 5.79e-09 ***
## phi.core 0.0927539 0.0059493 15.591 < 2e-16 ***
## FaciesF10 0.0896953 0.0945929 0.948 0.34330
## FaciesF2 0.0152576 0.1523676 0.100 0.92026
## FaciesF3 -0.0292379 0.0869197 -0.336 0.73667
## FaciesF5 0.1022238 0.0879087 1.163 0.24524
## FaciesF7 0.2794793 0.1462763 1.911 0.05641 .
## FaciesF8 -0.0932936 0.0927473 -1.006 0.31477
## FaciesF9 -0.3877078 0.1030388 -3.763 0.00018 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3339 on 802 degrees of freedom
## Multiple R-squared: 0.6787, Adjusted R-squared: 0.6722
## F-statistic: 105.9 on 16 and 802 DF, p-value: < 2.2e-16log_k.predicted_6 <-predict(model_6,data=data)
k.predicted_6<-10^log_k.predicted_6
plot(k.predicted_6,data$k.core)
Backward Stepwise Selection: Backward stepwise regression is performed
on model_5 to create model_6. Predictions and Plot: Predictions are made
using model_6, and these predictions are inverse-transformed and
compared to the actual values.
##Step 13: Calculate RMSE for Model 6
rmse_6<- RMSE(k.predicted_6,data$k.core )
rmse_6## [1] 1330.932RMSE Calculation: The RMSE for model_6 is computed to assess the performance of the log-transformed model after stepwise selection.
##Step 14: Split Data into Training and Testing Sets
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionset.seed(12345)
training<-sample_frac(data, .80)
testing<-anti_join(data,training)## Joining with `by = join_by(depth, caliper, ind.deep, ind.med, gamma, phi.N,
## R.deep, R.med, SP, density.corr, density, phi.core, k.core, Facies,
## phi.core.frac, log10_k.core)`Data Split: The dataset is split into training (80%) and testing (20%) sets. This is done using sample_frac() from the dplyr package, and anti_join() ensures that the testing set contains the remaining data
##Step 15: Build Model 7 - Linear Regression on Training Set
model_7<- lm(log10_k.core~.-k.core,data=training)
summary(model_7)##
## Call:
## lm(formula = log10_k.core ~ . - k.core, data = training)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.57123 -0.11876 0.02389 0.14325 0.79914
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.4732574 5.2931806 -0.467 0.64048
## depth 0.0007823 0.0005429 1.441 0.15013
## caliper -0.4661148 0.3064028 -1.521 0.12870
## ind.deep -0.0005275 0.0007083 -0.745 0.45671
## ind.med 0.0004756 0.0007769 0.612 0.54066
## gamma -0.0084138 0.0018608 -4.522 7.32e-06 ***
## phi.N -1.7476182 0.4515742 -3.870 0.00012 ***
## R.deep -0.0026534 0.0020047 -1.324 0.18611
## R.med 0.0046611 0.0028759 1.621 0.10557
## SP -0.0022459 0.0009607 -2.338 0.01972 *
## density.corr 1.6498996 1.3916437 1.186 0.23623
## density 1.5514223 0.3493920 4.440 1.06e-05 ***
## phi.core 0.0950263 0.0068555 13.861 < 2e-16 ***
## FaciesF10 0.0891010 0.1084215 0.822 0.41150
## FaciesF2 -0.0045917 0.1652854 -0.028 0.97785
## FaciesF3 -0.0705671 0.1022238 -0.690 0.49025
## FaciesF5 0.1276889 0.1055910 1.209 0.22701
## FaciesF7 0.3135309 0.1645276 1.906 0.05715 .
## FaciesF8 -0.1040710 0.1209194 -0.861 0.38975
## FaciesF9 -0.3722565 0.1340632 -2.777 0.00565 **
## phi.core.frac NA NA NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3399 on 635 degrees of freedom
## Multiple R-squared: 0.6689, Adjusted R-squared: 0.659
## F-statistic: 67.53 on 19 and 635 DF, p-value: < 2.2e-16log_k.predicted_7 <-predict(model_7,newdata=testing)
k.predicted_7<-10^log_k.predicted_7
plot(k.predicted_7,testing$k.core)
Model Creation: model_7 is built using the training set to predict the
log-transformed k.core. Predictions: Predictions are made on the testing
set (newdata = testing), then inverse-transformed. Plot: The predicted
values (k.predicted_7) are plotted against the actual values in the
testing set.
##Step 16: Calculate RMSE for Model 7
rmse_7<- RMSE(k.predicted_7,testing$k.core )
rmse_7## [1] 1619.041RMSE Calculation: The RMSE for model_7 is computed based on the predicted values (k.predicted_7) and the actual k.core values from the testing set. This helps to evaluate the model’s accuracy when making predictions on new, unseen data.
##Step 17: Build Model 8 - Backward Stepwise Regression on Model 7
model_8<-step(model_7, direction = "backward")## Start: AIC=-1394.04
## log10_k.core ~ (depth + caliper + ind.deep + ind.med + gamma +
## phi.N + R.deep + R.med + SP + density.corr + density + phi.core +
## k.core + Facies + phi.core.frac) - k.core
##
##
## Step: AIC=-1394.04
## log10_k.core ~ depth + caliper + ind.deep + ind.med + gamma +
## phi.N + R.deep + R.med + SP + density.corr + density + phi.core +
## Facies
##
## Df Sum of Sq RSS AIC
## - ind.med 1 0.0433 73.395 -1395.7
## - ind.deep 1 0.0641 73.416 -1395.5
## - density.corr 1 0.1624 73.514 -1394.6
## - R.deep 1 0.2024 73.554 -1394.2
## <none> 73.352 -1394.0
## - depth 1 0.2398 73.592 -1393.9
## - caliper 1 0.2673 73.619 -1393.7
## - R.med 1 0.3034 73.655 -1393.3
## - SP 1 0.6312 73.983 -1390.4
## - phi.N 1 1.7301 75.082 -1380.8
## - density 1 2.2776 75.629 -1376.0
## - gamma 1 2.3617 75.714 -1375.3
## - Facies 7 6.4874 79.839 -1352.5
## - phi.core 1 22.1943 95.546 -1222.9
##
## Step: AIC=-1395.65
## log10_k.core ~ depth + caliper + ind.deep + gamma + phi.N + R.deep +
## R.med + SP + density.corr + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - ind.deep 1 0.0759 73.471 -1397.0
## - R.deep 1 0.1888 73.584 -1396.0
## - density.corr 1 0.1974 73.593 -1395.9
## <none> 73.395 -1395.7
## - caliper 1 0.2469 73.642 -1395.5
## - R.med 1 0.2845 73.680 -1395.1
## - depth 1 0.3477 73.743 -1394.5
## - SP 1 0.6012 73.996 -1392.3
## - phi.N 1 1.7008 75.096 -1382.6
## - density 1 2.2803 75.676 -1377.6
## - gamma 1 2.3195 75.715 -1377.3
## - Facies 7 7.7978 81.193 -1343.5
## - phi.core 1 22.1551 95.550 -1224.9
##
## Step: AIC=-1396.97
## log10_k.core ~ depth + caliper + gamma + phi.N + R.deep + R.med +
## SP + density.corr + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - density.corr 1 0.1982 73.669 -1397.2
## - R.deep 1 0.2114 73.682 -1397.1
## <none> 73.471 -1397.0
## - depth 1 0.2718 73.743 -1396.5
## - R.med 1 0.3711 73.842 -1395.7
## - caliper 1 0.4138 73.885 -1395.3
## - SP 1 0.6465 74.118 -1393.2
## - phi.N 1 1.8773 75.348 -1382.5
## - density 1 2.4061 75.877 -1377.9
## - gamma 1 2.4768 75.948 -1377.2
## - Facies 7 7.7419 81.213 -1345.3
## - phi.core 1 22.2233 95.694 -1225.9
##
## Step: AIC=-1397.21
## log10_k.core ~ depth + caliper + gamma + phi.N + R.deep + R.med +
## SP + density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## - R.deep 1 0.2189 73.888 -1397.3
## <none> 73.669 -1397.2
## - depth 1 0.3370 74.006 -1396.2
## - caliper 1 0.3897 74.059 -1395.8
## - R.med 1 0.3941 74.063 -1395.7
## - SP 1 0.6070 74.276 -1393.8
## - phi.N 1 1.7504 75.420 -1383.8
## - gamma 1 2.3915 76.061 -1378.3
## - density 1 2.8893 76.559 -1374.0
## - Facies 7 7.9373 81.607 -1344.2
## - phi.core 1 22.0361 95.705 -1227.8
##
## Step: AIC=-1397.26
## log10_k.core ~ depth + caliper + gamma + phi.N + R.med + SP +
## density + phi.core + Facies
##
## Df Sum of Sq RSS AIC
## <none> 73.888 -1397.3
## - depth 1 0.2491 74.137 -1397.1
## - R.med 1 0.3477 74.236 -1396.2
## - caliper 1 0.3903 74.278 -1395.8
## - SP 1 0.5090 74.397 -1394.8
## - phi.N 1 1.8514 75.740 -1383.0
## - gamma 1 2.2934 76.182 -1379.2
## - density 1 2.7627 76.651 -1375.2
## - Facies 7 7.8761 81.764 -1344.9
## - phi.core 1 22.6856 96.574 -1223.9summary(model_8)##
## Call:
## lm(formula = log10_k.core ~ depth + caliper + gamma + phi.N +
## R.med + SP + density + phi.core + Facies, data = training)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.58792 -0.11365 0.02482 0.14757 0.76086
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.4288931 4.5051297 -0.317 0.7512
## depth 0.0006448 0.0004394 1.468 0.1427
## caliper -0.5199205 0.2830059 -1.837 0.0667 .
## gamma -0.0081181 0.0018229 -4.453 9.97e-06 ***
## phi.N -1.7577281 0.4392713 -4.001 7.03e-05 ***
## R.med 0.0015024 0.0008664 1.734 0.0834 .
## SP -0.0019650 0.0009366 -2.098 0.0363 *
## density 1.6440250 0.3363417 4.888 1.29e-06 ***
## phi.core 0.0940016 0.0067112 14.007 < 2e-16 ***
## FaciesF10 0.1191848 0.1069107 1.115 0.2654
## FaciesF2 0.0434273 0.1630734 0.266 0.7901
## FaciesF3 -0.0576872 0.0999261 -0.577 0.5639
## FaciesF5 0.1577376 0.0999557 1.578 0.1150
## FaciesF7 0.3390997 0.1567647 2.163 0.0309 *
## FaciesF8 -0.0573559 0.1056215 -0.543 0.5873
## FaciesF9 -0.3543834 0.1193547 -2.969 0.0031 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.34 on 639 degrees of freedom
## Multiple R-squared: 0.6665, Adjusted R-squared: 0.6587
## F-statistic: 85.14 on 15 and 639 DF, p-value: < 2.2e-16log_k.predicted_8 <-predict(model_8,newdata=testing)
k.predicted_8<-10^log_k.predicted_8
plot(k.predicted_8,testing$k.core)
Backward Stepwise Selection: Similar to earlier steps, backward stepwise
selection is applied to model_7 to create model_8. This removes the less
significant predictors, resulting in a more efficient model. Predictions
on Testing Set: The predict() function is used to generate predictions
(log_k.predicted_8) on the testing set using the simplified model. These
predictions are inverse-transformed back to the original scale
(k.predicted_8). Plot: A scatter plot is created to visualize the
predicted values (k.predicted_8) against the actual values
(testing$k.core) from the testing set.
##Step 18: Calculate RMSE for Model 8
rmse_8<- RMSE(k.predicted_8,testing$k.core )
rmse_8## [1] 1669.368RMSE Calculation: The RMSE for model_8 is calculated to evaluate its performance on the testing data. This allows for comparison with the previous models and helps to understand how much the model improved (or not) with backward selection.