library(wooldridge)
datosparcial_1 <- wooldridge::hprice2
print(datosparcial_1)## price crime nox rooms dist radial proptax stratio lowstat lprice
## 1 24000 0.006 5.38 6.57 4.09 1 29.6 15.3 4.98 10.085809
## 2 21599 0.027 4.69 6.42 4.97 2 24.2 17.8 9.14 9.980402
## 3 34700 0.027 4.69 7.18 4.97 2 24.2 17.8 4.03 10.454495
## 4 33400 0.032 4.58 7.00 6.06 3 22.2 18.7 2.94 10.416311
## 5 36199 0.069 4.58 7.15 6.06 3 22.2 18.7 5.33 10.496787
## 6 28701 0.030 4.58 6.43 6.06 3 22.2 18.7 5.21 10.264688
## 7 22900 0.088 5.24 6.01 5.56 5 31.1 15.2 12.43 10.038892
## 8 27100 0.145 5.24 6.17 5.95 5 31.1 15.2 19.15 10.207289
## 9 16500 0.211 5.24 5.63 6.08 5 31.1 15.2 29.93 9.711116
## 10 18900 0.170 5.24 6.00 6.59 5 31.1 15.2 17.10 9.846917
## 11 15000 0.225 5.24 6.38 6.35 5 31.1 15.2 20.45 9.615806
## 12 18900 0.117 5.24 6.01 6.23 5 31.1 15.2 13.27 9.846917
## 13 21700 0.094 5.24 5.89 5.45 5 31.1 15.2 15.71 9.985067
## 14 20400 0.630 5.38 5.95 4.71 4 30.7 21.0 8.26 9.923290
## 15 18200 0.638 5.38 6.10 4.46 4 30.7 21.0 10.26 9.809176
## 16 19900 0.627 5.38 5.83 4.50 4 30.7 21.0 8.47 9.898475
## 17 23100 1.054 5.38 5.93 4.50 4 30.7 21.0 6.58 10.047588
## 18 17500 0.784 5.38 5.99 4.26 4 30.7 21.0 14.67 9.769957
## 19 20200 0.803 5.38 5.46 3.80 4 30.7 21.0 11.69 9.913438
## 20 18200 0.726 5.38 5.73 3.80 4 30.7 21.0 11.28 9.809176
## 21 13600 1.252 5.38 5.57 3.80 4 30.7 21.0 21.02 9.517825
## 22 19600 0.852 5.38 5.96 4.01 4 30.7 21.0 13.83 9.883285
## 23 15200 1.232 5.38 6.14 3.98 4 30.7 21.0 18.72 9.629050
## 24 14500 0.988 5.38 5.81 4.10 4 30.7 21.0 19.88 9.581903
## 25 15600 0.750 5.38 5.92 4.40 4 30.7 21.0 16.30 9.655026
## 26 13900 0.841 5.38 5.60 4.45 4 30.7 21.0 16.51 9.539644
## 27 16600 0.672 5.38 5.81 4.68 4 30.7 21.0 14.81 9.717158
## 28 14800 0.956 5.38 6.05 4.45 4 30.7 21.0 17.28 9.602383
## 29 18400 0.773 5.38 6.49 4.45 4 30.7 21.0 12.80 9.820106
## 30 21000 1.002 5.38 6.67 4.23 4 30.7 21.0 11.98 9.952278
## 31 12700 1.131 5.38 5.69 4.23 4 30.7 21.0 22.60 9.449357
## 32 14500 1.355 5.38 6.07 4.17 4 30.7 21.0 13.04 9.581903
## 33 13200 1.388 5.38 5.95 3.99 4 30.7 21.0 27.71 9.487972
## 34 13100 1.152 5.38 5.70 3.79 4 30.7 21.0 18.35 9.480368
## 35 13500 1.613 5.38 6.10 3.76 4 30.7 21.0 20.34 9.510445
## 36 18900 0.064 4.99 5.93 3.36 5 27.9 19.2 9.68 9.846917
## 37 20000 0.097 4.99 5.84 3.38 5 27.9 19.2 11.41 9.903487
## 38 13668 0.080 4.99 5.85 3.93 5 27.9 19.2 8.77 9.522813
## 39 24701 0.175 4.99 5.97 3.85 5 27.9 19.2 10.13 10.114599
## 40 30801 0.028 4.28 6.59 5.40 3 25.2 18.3 4.32 10.335302
## 41 34899 0.034 4.28 7.02 5.40 3 25.2 18.3 1.98 10.460214
## 42 26601 0.127 4.48 6.77 5.72 3 23.3 17.9 4.84 10.188704
## 43 25301 0.141 4.48 6.17 5.72 3 23.3 17.9 5.81 10.138599
## 44 24701 0.159 4.48 6.21 5.72 3 23.3 17.9 7.44 10.114599
## 45 21200 0.123 4.48 6.07 5.72 3 23.3 17.9 9.55 9.961757
## 46 19300 0.171 4.48 5.68 5.10 3 23.3 17.9 10.21 9.867861
## 47 20000 0.188 4.48 5.79 5.10 3 23.3 17.9 14.15 9.903487
## 48 16600 0.229 4.48 6.03 5.69 3 23.3 17.9 18.80 9.717158
## 49 14400 0.254 4.48 5.40 5.87 3 23.3 17.9 30.81 9.574984
## 50 19400 0.220 4.48 5.60 6.09 3 23.3 17.9 16.20 9.873029
## 51 19700 0.089 4.39 5.96 6.81 4 24.3 16.8 13.45 9.888374
## 52 20500 0.043 4.39 6.11 6.81 4 24.3 16.8 9.43 9.928180
## 53 22620 0.054 4.39 6.51 6.81 4 24.3 16.8 5.28 10.026589
## 54 23400 0.050 4.39 6.00 6.81 4 24.3 21.1 8.43 10.060492
## 55 18900 0.014 4.10 5.89 7.32 3 46.9 17.9 14.80 9.846917
## 56 35401 0.013 4.03 7.25 8.70 5 22.6 17.3 4.81 10.474495
## 57 24701 0.021 4.10 6.38 9.19 2 31.3 15.1 5.77 10.114599
## 58 32562 0.014 4.11 6.82 8.32 5 25.6 19.7 3.95 10.390902
## 59 23300 0.154 4.53 6.14 7.81 8 28.4 19.7 6.86 10.056209
## 60 19600 0.103 4.53 5.93 6.93 8 28.4 19.7 9.22 9.883285
## 61 18700 0.149 4.53 5.74 6.76 8 28.4 19.7 13.15 9.836279
## 62 16000 0.172 4.53 5.97 6.82 8 28.4 19.7 14.44 9.680344
## 63 22199 0.110 4.53 6.46 7.23 8 28.4 19.7 6.73 10.007803
## 64 24999 0.127 4.53 6.76 7.98 8 28.4 19.7 9.50 10.126591
## 65 33001 0.020 4.16 7.10 9.22 3 21.6 18.6 8.05 10.404293
## 66 23501 0.036 3.98 6.29 6.61 4 33.7 16.1 4.67 10.064798
## 67 19400 0.044 3.98 5.79 6.61 4 33.7 16.1 10.24 9.873029
## 68 22000 0.058 4.09 5.88 6.50 4 34.5 18.9 8.10 9.998797
## 69 17400 0.136 4.09 5.59 6.50 4 34.5 18.9 13.09 9.764226
## 70 20900 0.128 4.09 5.88 6.50 4 34.5 18.9 8.79 9.947504
## 71 24200 0.088 4.13 6.42 5.29 4 30.5 19.2 6.72 10.094108
## 72 21700 0.159 4.13 5.96 5.29 4 30.5 19.2 9.88 9.985067
## 73 22800 0.092 4.13 6.06 5.29 4 30.5 19.2 5.52 10.034515
## 74 23400 0.195 4.13 6.24 5.29 4 30.5 19.2 7.54 10.060492
## 75 24101 0.079 4.37 6.27 4.25 5 39.8 18.7 6.78 10.090009
## 76 21400 0.095 4.37 6.29 4.50 5 39.8 18.7 8.94 9.971147
## 77 20000 0.102 4.37 6.28 4.05 5 39.8 18.7 11.97 9.903487
## 78 20800 0.087 4.37 6.14 4.09 5 39.8 18.7 10.27 9.942708
## 79 21200 0.056 4.37 6.23 5.01 5 39.8 18.7 12.34 9.961757
## 80 20300 0.084 4.37 5.87 4.50 5 39.8 18.7 9.10 9.918376
## 81 28001 0.041 4.26 6.73 5.40 4 28.1 19.0 5.29 10.239996
## 82 23899 0.045 4.26 6.62 5.40 4 28.1 19.0 7.22 10.081592
## 83 24800 0.037 4.26 6.30 5.40 4 28.1 19.0 6.72 10.118599
## 84 22900 0.036 4.26 6.17 5.40 4 28.1 19.0 7.51 10.038892
## 85 23899 0.051 4.49 6.39 4.78 3 24.7 18.5 9.62 10.081592
## 86 26601 0.057 4.49 6.63 4.44 3 24.7 18.5 6.53 10.188704
## 87 22501 0.052 4.49 6.01 4.43 3 24.7 18.5 12.86 10.021315
## 88 22199 0.072 4.49 6.12 3.75 3 24.7 18.5 8.44 10.007803
## 89 23600 0.057 4.89 7.01 3.42 2 27.0 17.8 5.50 10.069002
## 90 28701 0.053 4.89 7.08 3.41 2 27.0 17.8 5.70 10.264688
## 91 22600 0.047 4.89 6.42 3.09 2 27.0 17.8 8.81 10.025705
## 92 22000 0.039 4.89 6.40 3.09 2 27.0 17.8 8.20 9.998797
## 93 22900 0.042 4.64 6.44 3.67 4 27.0 18.2 8.16 10.038892
## 94 24999 0.029 4.64 6.21 3.67 4 27.0 18.2 6.21 10.126591
## 95 20600 0.043 4.64 6.25 3.61 4 27.0 18.2 10.59 9.933046
## 96 28399 0.122 4.45 6.62 3.50 2 27.6 18.0 6.65 10.254109
## 97 21400 0.115 4.45 6.16 3.50 2 27.6 18.0 11.34 9.971147
## 98 38700 0.121 4.45 8.07 3.50 2 27.6 18.0 4.21 10.563595
## 99 43800 0.082 4.45 7.82 3.50 2 27.6 18.0 3.57 10.687389
## 100 33200 0.069 4.45 7.42 3.50 2 27.6 18.0 6.19 10.410305
## 101 27499 0.149 5.20 6.73 2.78 5 38.4 20.9 9.42 10.221905
## 102 26500 0.114 5.20 6.78 2.86 5 38.4 20.9 7.67 10.184900
## 103 18600 0.229 5.20 6.40 2.71 5 38.4 20.9 10.63 9.830916
## 104 19300 0.212 5.20 6.14 2.71 5 38.4 20.9 13.44 9.867861
## 105 20100 0.140 5.20 6.17 2.42 5 38.4 20.9 12.33 9.908475
## 106 19500 0.133 5.20 5.85 2.11 5 38.4 20.9 16.47 9.878170
## 107 19500 0.171 5.20 5.84 2.21 5 38.4 20.9 18.66 9.878170
## 108 20400 0.131 5.20 6.13 2.12 5 38.4 20.9 14.09 9.923290
## 109 19800 0.128 5.20 6.47 2.43 5 38.4 20.9 12.27 9.893437
## 110 19400 0.264 5.20 6.23 2.55 5 38.4 20.9 15.55 9.873029
## 111 21700 0.108 5.47 6.19 2.78 5 38.4 20.9 13.00 9.985067
## 112 22800 0.101 5.47 6.71 2.68 6 43.2 17.8 10.16 10.034515
## 113 18800 0.123 5.47 5.91 2.35 6 43.2 17.8 16.21 9.841612
## 114 18700 0.222 5.47 6.09 2.63 6 43.2 17.8 17.09 9.836279
## 115 18500 0.142 5.47 6.25 2.26 6 43.2 17.8 10.45 9.825526
## 116 18300 0.171 5.47 5.93 2.46 6 43.2 17.8 15.76 9.814656
## 117 21200 0.132 5.47 6.18 2.73 6 43.2 17.8 12.04 9.961757
## 118 19200 0.151 5.47 6.02 2.75 6 43.2 17.8 10.30 9.862665
## 119 20400 0.131 5.47 5.87 2.48 6 43.2 17.8 15.37 9.923290
## 120 19300 0.145 5.81 5.73 2.76 6 43.2 17.8 13.61 9.867861
## 121 22000 0.069 5.81 5.87 2.26 2 18.8 19.1 39.07 9.998797
## 122 20300 0.072 5.81 6.00 2.20 2 18.8 19.1 14.27 9.918376
## 123 20500 0.093 5.81 5.96 2.09 2 18.8 19.1 17.93 9.928180
## 124 17300 0.150 5.81 5.86 1.94 2 18.8 19.1 25.41 9.758462
## 125 18800 0.098 5.81 5.88 2.01 2 18.8 19.1 17.58 9.841612
## 126 21400 0.169 5.81 5.99 1.99 2 18.8 19.1 14.81 9.971147
## 127 15700 0.387 6.24 5.61 1.76 2 18.8 19.1 27.26 9.661416
## 128 16200 0.259 6.24 5.69 1.79 4 43.7 21.2 17.19 9.692766
## 129 18000 0.325 6.24 6.43 1.81 4 43.7 21.2 15.39 9.798127
## 130 14300 0.881 6.24 5.64 1.98 4 43.7 21.2 18.34 9.568015
## 131 19200 0.340 6.24 6.46 2.12 4 43.7 21.2 12.60 9.862665
## 132 19600 1.193 6.24 6.33 2.27 4 43.7 21.2 12.26 9.883285
## 133 23001 0.590 6.24 6.37 2.33 4 43.7 21.2 11.12 10.043293
## 134 18400 0.330 6.24 5.82 2.47 4 43.7 21.2 15.03 9.820106
## 135 15600 0.976 6.24 5.76 2.35 4 43.7 21.2 17.31 9.655026
## 136 18100 0.558 6.24 6.33 2.11 4 43.7 21.2 16.96 9.803667
## 137 17400 0.323 6.24 5.94 1.97 4 43.7 21.2 16.90 9.764226
## 138 17100 0.352 6.24 6.45 1.85 4 43.7 21.2 14.59 9.746834
## 139 13300 0.250 6.24 5.86 1.67 4 43.7 21.2 21.32 9.495520
## 140 17800 0.545 6.24 6.15 1.67 4 43.7 21.2 18.46 9.786954
## 141 14000 0.291 6.24 6.17 1.61 4 43.7 21.2 24.16 9.546813
## 142 14400 1.629 6.24 5.02 1.44 4 43.7 21.2 34.41 9.574984
## 143 13400 3.321 8.71 5.40 1.32 5 40.3 14.7 26.82 9.503010
## 144 15600 4.097 8.71 5.47 1.41 5 40.3 14.7 26.42 9.655026
## 145 11800 2.780 8.71 4.90 1.35 5 40.3 14.7 29.29 9.375854
## 146 13800 2.379 8.71 6.13 1.42 5 40.3 14.7 27.80 9.532424
## 147 15600 2.155 8.71 5.63 1.52 5 40.3 14.7 16.65 9.655026
## 148 14600 2.369 8.71 4.93 1.46 5 40.3 14.7 29.53 9.588777
## 149 17794 2.331 8.71 5.19 1.53 5 40.3 14.7 28.32 9.786616
## 150 15400 2.734 8.71 5.60 1.53 5 40.3 14.7 21.45 9.642123
## 151 21500 1.657 8.71 6.12 1.62 5 40.3 14.7 14.10 9.975808
## 152 19600 1.496 8.71 5.40 1.59 5 40.3 14.7 13.28 9.883285
## 153 15300 1.127 8.71 5.01 1.61 5 40.3 14.7 12.12 9.635608
## 154 19400 3.149 8.71 5.71 1.62 5 40.3 14.7 15.79 9.873029
## 155 17000 1.414 8.71 6.13 1.75 5 40.3 14.7 15.12 9.740969
## 156 15600 3.535 8.71 6.15 1.75 5 40.3 14.7 15.02 9.655026
## 157 13100 2.447 8.71 5.27 1.74 5 40.3 14.7 16.14 9.480368
## 158 41299 1.224 6.05 6.94 1.88 5 40.3 14.7 4.59 10.628593
## 159 24299 1.343 6.05 6.07 1.76 5 40.3 14.7 6.43 10.098190
## 160 23300 1.425 8.71 6.51 1.77 5 40.3 14.7 7.39 10.056209
## 161 27000 1.273 6.05 6.25 1.80 5 40.3 14.7 5.50 10.203592
## 162 50001 1.463 6.05 7.49 1.97 5 40.3 14.7 1.73 10.819798
## 163 50001 1.834 6.05 7.80 2.04 5 40.3 14.7 1.92 10.819798
## 164 50001 1.519 6.05 8.37 2.16 5 40.3 14.7 3.32 10.819798
## 165 22700 2.242 6.05 5.85 2.42 5 40.3 14.7 11.64 10.030120
## 166 24999 2.924 6.05 6.10 2.28 5 40.3 14.7 9.81 10.126591
## 167 50001 2.010 6.05 7.93 2.05 5 40.3 14.7 3.70 10.819798
## 168 23799 1.800 6.05 5.88 2.43 5 40.3 14.7 12.14 10.077399
## 169 23799 2.300 6.05 6.32 2.10 5 40.3 14.7 11.09 10.077399
## 170 22299 2.450 6.05 6.40 2.26 5 40.3 14.7 11.32 10.012297
## 171 17400 1.207 6.05 5.87 2.43 5 40.3 14.7 14.43 9.764226
## 172 19100 2.314 6.05 5.88 2.39 5 40.3 14.7 12.03 9.857444
## 173 23100 0.139 5.10 5.57 2.60 5 29.6 16.6 14.69 10.047588
## 174 23600 0.092 5.10 6.42 2.65 5 29.6 16.6 9.04 10.069002
## 175 22600 0.084 5.10 5.86 2.70 5 29.6 16.6 9.64 10.025705
## 176 29401 0.067 5.10 6.55 3.13 5 29.6 16.6 5.33 10.288784
## 177 23200 0.070 5.10 6.02 3.55 5 29.6 16.6 10.11 10.051908
## 178 24600 0.054 5.10 6.31 3.30 5 29.6 16.6 6.29 10.110501
## 179 29900 0.066 5.10 6.86 2.91 5 29.6 16.6 6.92 10.305614
## 180 37201 0.058 4.88 6.98 2.83 3 19.3 17.8 5.04 10.524091
## 181 39799 0.066 4.88 7.76 2.74 3 19.3 17.8 7.56 10.591597
## 182 36199 0.069 4.88 6.14 2.60 3 19.3 17.8 9.45 10.496787
## 183 37900 0.091 4.88 7.15 2.70 3 19.3 17.8 4.82 10.542706
## 184 32500 0.100 4.88 6.56 2.85 3 19.3 17.8 5.68 10.388995
## 185 26399 0.083 4.88 5.60 2.99 3 19.3 17.8 13.98 10.181082
## 186 29599 0.060 4.88 6.15 3.28 3 19.3 17.8 13.15 10.295496
## 187 50001 0.056 4.88 7.83 3.20 3 19.3 17.8 4.45 10.819798
## 188 32000 0.079 4.37 6.78 3.79 5 39.8 15.2 6.68 10.373491
## 189 29801 0.126 4.37 6.56 4.57 5 39.8 15.2 4.56 10.302298
## 190 34899 0.084 4.37 7.18 4.57 5 39.8 15.2 5.39 10.460214
## 191 37001 0.091 4.37 6.95 6.48 5 39.8 15.2 5.10 10.518701
## 192 30501 0.069 4.37 6.74 6.48 5 39.8 15.2 4.69 10.325515
## 193 36399 0.087 4.37 7.18 6.48 5 39.8 15.2 2.87 10.502296
## 194 31101 0.022 4.01 6.80 6.22 1 26.5 15.6 5.03 10.344995
## 195 29100 0.014 4.01 6.60 6.22 1 26.5 15.6 4.38 10.278494
## 196 50001 0.014 4.22 7.87 5.65 4 25.5 14.4 2.97 10.819798
## 197 33300 0.040 4.04 7.29 7.31 2 32.9 12.6 4.08 10.413313
## 198 30300 0.047 4.04 7.11 7.31 2 32.9 12.6 8.61 10.318903
## 199 34600 0.038 4.04 7.27 7.31 2 32.9 12.6 6.62 10.451609
## 200 34899 0.032 4.03 6.97 7.65 3 40.2 17.0 4.56 10.460214
## 201 32899 0.018 4.03 7.13 7.65 3 40.2 17.0 4.45 10.401197
## 202 24101 0.034 4.15 6.16 6.27 2 34.8 14.7 7.43 10.090009
## 203 42302 0.022 4.15 7.61 6.27 2 34.8 14.7 3.11 10.652590
## 204 48499 0.035 4.16 7.85 5.12 4 22.4 14.7 3.81 10.789298
## 205 50001 0.020 4.16 8.03 5.12 4 22.4 14.7 2.88 10.819798
## 206 22600 0.136 4.89 5.89 3.95 4 27.7 18.6 10.87 10.025705
## 207 24399 0.230 4.89 6.33 4.35 4 27.7 18.6 10.97 10.102298
## 208 22501 0.252 4.89 5.78 4.35 4 27.7 18.6 18.06 10.021315
## 209 24399 0.136 4.89 6.06 4.24 4 27.7 18.6 14.66 10.102298
## 210 20000 0.436 4.89 5.34 3.87 4 27.7 18.6 23.09 9.903487
## 211 21700 0.174 4.89 5.96 3.88 4 27.7 18.6 17.27 9.985067
## 212 19300 0.376 4.89 5.40 3.67 4 27.7 18.6 23.98 9.867861
## 213 22400 0.217 4.89 5.81 3.65 4 27.7 18.6 16.03 10.016816
## 214 28099 0.141 4.89 6.37 3.95 4 27.7 18.6 9.38 10.243489
## 215 23699 0.290 4.89 5.41 3.59 4 27.7 18.6 29.55 10.073188
## 216 24999 0.198 4.89 6.18 3.95 4 27.7 18.6 9.47 10.126591
## 217 23300 0.046 5.50 5.89 3.11 5 27.6 16.4 13.51 10.056209
## 218 28701 0.070 5.50 6.64 3.42 5 27.6 16.4 9.69 10.264688
## 219 21500 0.111 5.50 5.95 2.89 5 27.6 16.4 17.92 9.975808
## 220 23001 0.114 5.50 6.37 3.36 5 27.6 16.4 10.50 10.043293
## 221 26699 0.358 5.07 6.95 2.86 8 30.7 16.4 9.71 10.192382
## 222 21700 0.408 5.07 6.16 3.05 8 30.7 17.4 21.46 9.985067
## 223 27499 0.624 5.07 6.88 3.27 8 30.7 17.4 9.93 10.221905
## 224 30101 0.615 5.07 6.62 3.27 8 30.7 17.4 7.60 10.312314
## 225 44802 0.315 5.04 8.27 2.89 8 30.7 17.4 4.14 10.710008
## 226 50001 0.523 5.04 8.72 2.89 8 30.7 17.4 4.92 10.819798
## 227 37602 0.382 5.04 8.04 3.22 8 30.7 17.4 3.13 10.534813
## 228 31600 0.412 5.04 7.16 3.22 8 30.7 17.4 6.36 10.360912
## 229 46700 0.298 5.04 7.69 3.38 8 30.7 17.4 3.92 10.751499
## 230 31499 0.442 5.04 6.55 3.38 8 30.7 17.4 3.76 10.357711
## 231 24299 0.537 5.04 5.98 3.67 8 30.7 17.4 11.65 10.098190
## 232 31701 0.463 5.04 7.41 3.67 8 30.7 17.4 5.25 10.364103
## 233 41702 0.575 5.07 8.34 3.84 8 30.7 17.4 2.47 10.638305
## 234 48301 0.331 5.07 8.25 3.65 8 30.7 17.4 3.95 10.785208
## 235 29001 0.448 5.07 6.73 3.65 8 30.7 17.4 8.05 10.275085
## 236 24000 0.330 5.07 6.09 3.65 8 30.7 17.4 10.88 10.085809
## 237 25099 0.521 5.07 6.63 4.15 8 30.7 17.4 9.54 10.130583
## 238 31499 0.512 5.07 7.36 4.15 8 30.7 17.4 4.73 10.357711
## 239 23699 0.082 4.28 6.48 6.19 6 30.0 16.6 6.36 10.073188
## 240 23300 0.093 4.28 6.61 6.19 6 30.0 16.6 7.37 10.056209
## 241 22000 0.113 4.28 6.90 6.34 6 30.0 16.6 11.38 9.998797
## 242 20100 0.106 4.28 6.09 6.34 6 30.0 16.6 12.40 9.908475
## 243 22199 0.103 4.28 6.36 7.04 6 30.0 16.6 11.22 10.007803
## 244 23699 0.126 4.28 6.39 7.04 6 30.0 16.6 5.19 10.073188
## 245 17600 0.206 4.31 5.59 7.95 7 33.0 19.1 12.50 9.775654
## 246 18500 0.191 4.31 5.60 7.95 7 33.0 19.1 18.46 9.825526
## 247 24299 0.340 4.31 6.11 8.06 7 33.0 19.1 9.16 10.098190
## 248 20500 0.197 4.31 6.23 8.06 7 33.0 19.1 10.15 9.928180
## 249 24499 0.164 4.31 6.43 7.83 7 33.0 19.1 9.52 10.106387
## 250 26200 0.191 4.31 6.72 7.83 7 33.0 19.1 6.56 10.173514
## 251 24399 0.140 4.31 6.49 7.40 7 33.0 19.1 5.90 10.102298
## 252 24800 0.214 4.31 6.44 7.40 7 33.0 19.1 3.59 10.118599
## 253 29599 0.082 4.31 6.96 8.91 7 33.0 19.1 3.53 10.295496
## 254 42800 0.369 4.31 8.26 8.91 7 33.0 19.1 3.54 10.664293
## 255 21900 0.048 3.92 6.11 9.22 1 31.5 16.4 6.57 9.994242
## 256 20900 0.035 3.92 5.88 9.22 1 31.5 16.4 9.25 9.947504
## 257 43998 0.015 3.94 7.45 6.34 3 24.4 15.9 3.11 10.691899
## 258 50001 0.612 6.47 8.70 1.80 5 26.4 13.0 5.12 10.819798
## 259 36001 0.664 6.47 7.33 1.89 5 26.4 13.0 7.79 10.491302
## 260 30101 0.657 6.47 6.84 2.01 5 26.4 13.0 6.90 10.312314
## 261 33799 0.540 6.47 7.20 2.11 5 26.4 13.0 9.59 10.428186
## 262 43101 0.534 6.47 7.52 2.14 5 26.4 13.0 7.26 10.671302
## 263 48801 0.520 6.47 8.40 2.29 5 26.4 13.0 5.91 10.795506
## 264 30999 0.825 6.47 7.33 2.08 5 26.4 13.0 11.25 10.341710
## 265 36501 0.550 6.47 7.21 1.93 5 26.4 13.0 8.10 10.505095
## 266 22800 0.762 6.47 5.56 1.99 5 26.4 13.0 10.45 10.034515
## 267 30699 0.786 6.47 7.01 2.13 5 26.4 13.0 14.79 10.331985
## 268 50001 0.578 5.75 8.30 2.42 5 26.4 13.0 7.44 10.819798
## 269 43499 0.540 5.75 7.47 2.87 5 26.4 13.0 3.16 10.680493
## 270 20700 0.091 4.64 5.92 3.92 3 22.3 18.6 13.65 9.937889
## 271 21100 0.299 4.64 5.86 4.43 3 22.3 18.6 13.00 9.957028
## 272 25200 0.162 4.64 6.24 4.43 3 22.3 18.6 6.59 10.134600
## 273 24399 0.115 4.64 6.54 3.92 3 22.3 18.6 7.73 10.102298
## 274 35200 0.222 4.64 7.69 4.37 3 22.3 18.6 6.58 10.468801
## 275 32400 0.056 4.47 6.76 4.08 4 25.4 17.6 3.53 10.385914
## 276 32000 0.096 4.47 6.85 4.27 4 25.4 17.6 2.98 10.373491
## 277 33200 0.105 4.47 7.27 4.79 4 25.4 17.6 6.05 10.410305
## 278 33100 0.061 4.47 6.83 4.86 4 25.4 17.6 4.16 10.407289
## 279 29100 0.080 4.47 6.48 4.14 4 25.4 17.6 7.19 10.278494
## 280 35102 0.210 4.43 6.81 4.10 5 21.6 14.9 4.85 10.466013
## 281 45401 0.036 4.43 7.82 4.69 5 21.6 14.9 3.76 10.723289
## 282 35401 0.037 4.43 6.97 5.24 5 21.6 14.9 4.59 10.474495
## 283 46000 0.061 4.43 7.64 5.21 5 21.6 14.9 3.01 10.736397
## 284 50001 0.015 4.01 7.92 5.89 1 19.8 13.6 3.16 10.819798
## 285 32199 0.009 4.00 7.09 7.31 1 28.5 15.3 7.85 10.379691
## 286 22000 0.011 3.89 6.45 7.31 1 30.0 15.3 8.23 9.998797
## 287 20100 0.020 3.85 6.23 9.09 1 24.1 18.2 12.93 9.908475
## 288 23200 0.039 4.05 6.21 7.32 6 29.3 16.6 7.14 10.051908
## 289 22299 0.046 4.05 6.31 7.32 6 29.3 16.6 7.60 10.012297
## 290 24800 0.043 4.05 6.56 7.32 6 29.3 16.6 9.51 10.118599
## 291 28501 0.035 4.11 6.86 5.12 4 24.5 19.2 3.33 10.257694
## 292 37298 0.079 4.11 7.15 5.12 4 24.5 19.2 3.56 10.526695
## 293 27901 0.036 4.11 6.63 5.12 4 24.5 19.2 4.70 10.236418
## 294 23899 0.083 4.37 6.13 5.50 4 28.9 16.0 8.58 10.081592
## 295 21700 0.082 4.37 6.01 5.50 4 28.9 16.0 10.40 9.985067
## 296 28601 0.129 4.37 6.68 5.96 4 28.9 16.0 6.27 10.261197
## 297 27100 0.054 4.37 6.55 5.96 4 28.9 16.0 7.39 10.207289
## 298 20300 0.141 4.37 5.79 6.32 4 28.9 16.0 15.84 9.918376
## 299 22501 0.065 4.00 6.34 7.83 5 35.8 14.8 4.97 10.021315
## 300 29001 0.056 4.00 7.04 7.83 5 35.8 14.8 4.74 10.275085
## 301 24800 0.044 4.00 6.87 7.83 5 35.8 14.8 6.07 10.118599
## 302 22000 0.035 4.33 6.59 5.49 7 32.9 16.1 9.50 9.998797
## 303 26399 0.093 4.33 6.49 5.49 7 32.9 16.1 8.67 10.181082
## 304 33100 0.100 4.72 6.98 5.49 7 32.9 16.1 4.86 10.407289
## 305 36098 0.055 4.72 7.24 4.02 7 22.2 18.4 6.93 10.493993
## 306 28399 0.055 4.72 6.62 3.37 7 22.2 18.4 8.93 10.254109
## 307 33400 0.075 4.72 7.42 3.10 7 22.2 18.4 6.47 10.416311
## 308 28201 0.049 4.72 6.85 3.18 7 22.2 18.4 7.53 10.247112
## 309 22800 0.493 5.44 6.63 3.32 4 30.4 18.4 4.54 10.034515
## 310 20300 0.349 5.44 5.97 3.10 4 30.4 18.4 9.97 9.918376
## 311 16100 2.635 5.44 4.97 2.52 4 30.4 18.4 12.64 9.686575
## 312 22099 0.790 5.44 6.12 2.64 4 30.4 18.4 5.98 10.003287
## 313 19400 0.262 5.44 6.02 2.83 4 30.4 18.4 11.72 9.873029
## 314 21600 0.269 5.44 6.27 3.26 4 30.4 18.4 7.90 9.980449
## 315 23799 0.369 5.44 6.57 3.60 4 30.4 18.4 9.28 10.077399
## 316 16200 0.254 5.44 5.70 3.95 4 30.4 18.4 11.50 9.692766
## 317 17800 0.318 5.44 5.91 4.00 4 30.4 18.4 18.33 9.786954
## 318 19800 0.245 5.44 5.78 4.03 4 30.4 18.4 15.94 9.893437
## 319 23100 0.402 5.44 6.38 3.53 4 30.4 18.4 10.36 10.047588
## 320 21000 0.475 5.44 6.11 4.00 4 30.4 18.4 12.73 9.952278
## 321 23799 0.168 4.93 6.43 4.54 5 28.7 19.6 7.20 10.077399
## 322 23100 0.182 4.93 6.38 4.54 5 28.7 19.6 6.87 10.047588
## 323 20400 0.351 4.93 6.04 4.72 5 28.7 19.6 7.70 9.923290
## 324 18500 0.284 4.93 5.71 4.72 5 28.7 19.6 11.74 9.825526
## 325 24999 0.341 4.93 6.41 4.72 5 28.7 19.6 6.12 10.126591
## 326 24600 0.192 4.93 6.43 5.42 5 28.7 19.6 5.08 10.110501
## 327 23001 0.303 4.93 6.31 5.42 5 28.7 19.6 6.15 10.043293
## 328 22199 0.241 4.93 6.08 5.42 5 28.7 19.6 12.79 10.007803
## 329 19300 0.066 4.60 5.87 5.21 4 43.0 16.9 9.97 9.867861
## 330 22600 0.067 4.60 6.33 5.21 4 43.0 16.9 7.34 10.025705
## 331 19800 0.045 4.60 6.14 5.87 4 43.0 16.9 9.09 9.893437
## 332 17100 0.050 4.38 5.71 6.64 1 30.4 16.9 12.43 9.746834
## 333 19400 0.035 4.38 6.03 7.27 1 30.4 16.9 7.83 9.873029
## 334 22199 0.051 5.15 6.32 6.46 5 22.4 20.2 5.68 10.007803
## 335 20700 0.037 5.15 6.31 6.46 5 22.4 20.2 6.75 9.937889
## 336 21100 0.040 5.15 6.04 5.99 5 22.4 20.2 8.01 9.957028
## 337 19500 0.034 5.15 5.87 5.23 5 22.4 20.2 9.80 9.878170
## 338 18500 0.030 5.15 5.89 5.61 5 22.4 20.2 10.56 9.825526
## 339 20548 0.033 5.15 6.06 4.81 5 22.4 20.2 8.51 9.930519
## 340 19000 0.055 5.15 5.98 4.81 5 22.4 20.2 9.74 9.852194
## 341 18700 0.062 5.15 5.97 4.81 5 22.4 20.2 9.29 9.836279
## 342 32778 0.013 4.42 7.24 7.04 1 28.4 15.5 5.49 10.397512
## 343 16500 0.025 5.18 6.54 6.27 1 42.2 15.9 8.65 9.711116
## 344 23899 0.025 4.84 6.70 5.73 5 37.0 17.6 7.18 10.081592
## 345 31201 0.030 4.84 6.87 6.47 5 37.0 17.6 4.61 10.348206
## 346 17500 0.031 4.42 6.01 8.01 3 35.2 18.8 10.53 9.769957
## 347 17200 0.062 4.42 5.90 8.01 3 35.2 18.8 12.67 9.752665
## 348 23100 0.019 4.29 6.52 8.54 4 35.1 17.9 6.36 10.047588
## 349 24499 0.015 4.35 6.63 8.34 4 28.0 17.0 5.99 10.106387
## 350 26601 0.029 4.29 6.94 8.79 1 33.5 19.7 5.89 10.188704
## 351 22900 0.062 4.29 6.49 8.79 1 33.5 19.7 5.98 10.038892
## 352 24101 0.079 4.11 6.58 10.71 4 41.1 18.3 5.49 10.090009
## 353 18600 0.072 4.11 5.88 10.71 4 41.1 18.3 7.79 9.830916
## 354 30101 0.017 4.10 6.73 12.13 5 18.7 17.0 4.50 10.312314
## 355 18200 0.043 4.13 5.66 10.59 4 33.4 22.0 8.05 9.809176
## 356 20600 0.107 4.13 5.94 10.59 4 33.4 22.0 5.57 9.933046
## 357 17794 8.983 7.70 6.21 2.12 24 66.6 20.2 17.60 9.786616
## 358 21700 3.850 7.70 6.39 2.51 24 66.6 20.2 13.27 9.985067
## 359 22700 5.202 7.70 6.13 2.72 24 66.6 20.2 11.48 10.030120
## 360 22600 4.261 7.70 6.11 2.51 24 66.6 20.2 12.67 10.025705
## 361 24999 4.542 7.70 6.40 2.52 24 66.6 20.2 7.79 10.126591
## 362 19900 3.837 7.70 6.25 2.30 24 66.6 20.2 14.19 9.898475
## 363 20800 3.678 7.70 5.36 2.10 24 66.6 20.2 10.19 9.942708
## 364 16800 4.222 7.70 5.80 1.90 24 66.6 20.2 14.64 9.729135
## 365 21900 3.474 7.18 8.78 1.90 24 66.6 20.2 5.29 9.994242
## 366 27499 4.556 7.18 3.56 1.61 24 66.6 20.2 7.12 10.221905
## 367 21900 3.697 7.18 4.96 1.75 24 66.6 20.2 14.00 9.994242
## 368 23100 13.522 6.31 3.86 1.51 24 66.6 20.2 13.33 10.047588
## 369 50001 4.898 6.31 4.97 1.33 24 66.6 20.2 3.26 10.819798
## 370 50001 5.670 6.31 6.68 1.36 24 66.6 20.2 3.73 10.819798
## 371 50001 6.539 6.31 7.02 1.20 24 66.6 20.2 2.96 10.819798
## 372 50001 9.232 6.31 6.22 1.17 24 66.6 20.2 9.53 10.819798
## 373 50001 8.267 6.68 5.87 1.13 24 66.6 20.2 8.88 10.819798
## 374 13800 11.108 6.68 4.91 1.17 24 66.6 20.2 34.77 9.532424
## 375 13800 18.498 6.68 4.14 1.14 24 66.6 20.2 37.97 9.532424
## 376 15000 19.609 6.71 7.31 1.32 24 66.6 20.2 13.44 9.615806
## 377 13900 15.288 6.71 6.65 1.34 24 66.6 20.2 23.24 9.539644
## 378 13300 9.823 6.71 6.79 1.36 24 66.6 20.2 21.24 9.495520
## 379 13100 23.648 6.71 6.38 1.39 24 66.6 20.2 23.69 9.480368
## 380 10200 17.867 6.71 6.22 1.39 24 66.6 20.2 21.78 9.230143
## 381 10400 88.976 6.71 6.97 1.42 24 66.6 20.2 17.21 9.249561
## 382 10900 15.874 6.71 6.54 1.52 24 66.6 20.2 21.08 9.296518
## 383 11300 9.187 7.00 5.54 1.58 24 66.6 20.2 23.60 9.332558
## 384 12300 7.992 7.00 5.52 1.53 24 66.6 20.2 24.56 9.417355
## 385 8800 20.085 7.00 4.37 1.44 24 66.6 20.2 30.63 9.082507
## 386 7200 16.812 7.00 5.28 1.43 24 66.6 20.2 30.81 8.881836
## 387 10500 24.394 7.00 4.65 1.47 24 66.6 20.2 28.28 9.259130
## 388 7400 22.597 7.00 5.00 1.52 24 66.6 20.2 31.99 8.909235
## 389 10200 14.334 7.00 4.88 1.59 24 66.6 20.2 30.62 9.230143
## 390 11500 8.152 7.00 5.39 1.73 24 66.6 20.2 20.85 9.350102
## 391 15100 6.962 7.00 5.71 1.93 24 66.6 20.2 17.11 9.622450
## 392 23200 5.293 7.00 6.05 2.17 24 66.6 20.2 18.76 10.051908
## 393 9700 11.578 7.00 5.04 1.77 24 66.6 20.2 25.68 9.179881
## 394 13800 8.645 6.93 6.19 1.79 24 66.6 20.2 15.17 9.532424
## 395 12700 13.360 6.93 5.89 1.78 24 66.6 20.2 16.35 9.449357
## 396 13100 8.717 6.93 6.47 1.73 24 66.6 20.2 17.12 9.480368
## 397 12500 5.872 6.93 6.40 1.68 24 66.6 20.2 19.37 9.433484
## 398 8500 7.672 6.93 5.75 1.63 24 66.6 20.2 19.92 9.047821
## 399 5000 38.352 6.93 5.45 1.49 24 66.6 20.2 30.59 8.517193
## 400 6300 9.917 6.93 5.85 1.50 24 66.6 20.2 29.97 8.748305
## 401 5600 25.046 6.93 5.99 1.59 24 66.6 20.2 27.04 8.630522
## 402 7200 14.236 6.93 6.34 1.57 24 66.6 20.2 20.32 8.881836
## 403 12100 9.596 6.93 6.40 1.64 24 66.6 20.2 20.31 9.400961
## 404 8300 24.802 6.93 5.35 1.70 24 66.6 20.2 19.77 9.024011
## 405 8500 41.529 6.93 5.53 1.61 24 66.6 20.2 27.38 9.047821
## 406 5000 67.921 6.93 5.68 1.43 24 66.6 20.2 22.98 8.517193
## 407 11900 20.716 6.59 4.14 1.18 24 66.6 20.2 23.34 9.384294
## 408 27901 11.951 6.59 5.61 1.29 24 66.6 20.2 12.13 10.236418
## 409 17200 7.404 5.97 5.62 1.45 24 66.6 20.2 26.40 9.752665
## 410 27499 14.438 5.97 6.85 1.47 24 66.6 20.2 19.78 10.221905
## 411 15000 51.136 5.97 5.76 1.41 24 66.6 20.2 10.11 9.615806
## 412 17200 14.051 5.97 6.66 1.53 24 66.6 20.2 21.22 9.752665
## 413 17900 18.811 5.97 4.63 1.55 24 66.6 20.2 34.37 9.792556
## 414 16300 26.656 5.97 5.15 1.59 24 66.6 20.2 20.08 9.698920
## 415 7012 45.746 6.93 4.52 1.66 24 66.6 20.2 36.98 8.855378
## 416 7200 18.085 6.79 6.43 1.83 24 66.6 20.2 29.05 8.881836
## 417 7500 10.834 6.79 6.78 1.82 24 66.6 20.2 25.79 8.922658
## 418 10400 25.941 6.79 5.30 1.65 24 66.6 20.2 26.64 9.249561
## 419 8800 73.534 6.79 5.96 1.80 24 66.6 20.2 20.62 9.082507
## 420 8400 11.812 7.18 6.82 1.79 24 66.6 20.2 22.74 9.035987
## 421 16700 11.087 7.18 6.41 1.86 24 66.6 20.2 15.02 9.723164
## 422 14200 7.023 7.18 6.01 1.87 24 66.6 20.2 15.70 9.560997
## 423 20800 12.048 6.14 5.65 1.95 24 66.6 20.2 14.10 9.942708
## 424 13400 7.050 6.14 6.10 2.02 24 66.6 20.2 23.29 9.503010
## 425 11700 8.792 5.84 5.56 2.06 24 66.6 20.2 17.16 9.367344
## 426 8300 15.860 6.79 5.90 1.91 24 66.6 20.2 24.39 9.024011
## 427 10200 12.247 5.84 5.84 2.00 24 66.6 20.2 15.69 9.230143
## 428 10900 37.662 6.79 6.20 1.86 24 66.6 20.2 14.52 9.296518
## 429 11000 7.367 6.79 6.19 1.94 24 66.6 20.2 21.52 9.305651
## 430 9500 9.339 6.79 6.38 1.97 24 66.6 20.2 24.08 9.159047
## 431 14500 8.492 5.84 6.35 2.05 24 66.6 20.2 17.64 9.581903
## 432 14100 10.062 5.84 6.83 2.09 24 66.6 20.2 19.69 9.553930
## 433 16100 6.444 5.84 6.42 2.20 24 66.6 20.2 12.03 9.686575
## 434 14300 5.581 7.13 6.44 2.32 24 66.6 20.2 16.22 9.568015
## 435 11700 13.913 7.13 6.21 2.22 24 66.6 20.2 15.17 9.367344
## 436 13400 11.160 7.40 6.63 2.12 24 66.6 20.2 23.27 9.503010
## 437 9600 14.421 7.40 6.46 2.00 24 66.6 20.2 18.05 9.169518
## 438 8700 15.177 7.40 6.15 1.91 24 66.6 20.2 26.45 9.071078
## 439 8400 13.678 7.40 5.93 1.82 24 66.6 20.2 34.02 9.035987
## 440 12800 9.391 7.40 5.63 1.82 24 66.6 20.2 22.88 9.457200
## 441 10500 22.051 7.40 5.82 1.87 24 66.6 20.2 22.11 9.259130
## 442 17100 9.724 7.40 6.41 2.07 24 66.6 20.2 19.52 9.746834
## 443 18400 5.666 7.40 6.22 2.00 24 66.6 20.2 16.59 9.820106
## 444 15400 9.967 7.40 6.48 1.98 24 66.6 20.2 18.85 9.642123
## 445 10800 12.802 7.40 5.85 1.90 24 66.6 20.2 23.79 9.287301
## 446 11800 10.672 7.40 6.46 1.99 24 66.6 20.2 23.98 9.375854
## 447 14900 6.288 7.40 6.34 2.07 24 66.6 20.2 17.79 9.609117
## 448 12600 9.925 7.40 6.25 2.20 24 66.6 20.2 16.44 9.441452
## 449 14100 9.329 7.13 6.18 2.26 24 66.6 20.2 18.13 9.553930
## 450 13000 7.526 7.13 6.42 2.19 24 66.6 20.2 19.31 9.472705
## 451 13400 6.718 7.13 6.75 2.32 24 66.6 20.2 17.44 9.503010
## 452 15200 5.441 7.13 6.65 2.36 24 66.6 20.2 17.73 9.629050
## 453 16100 5.090 7.13 6.30 2.37 24 66.6 20.2 17.27 9.686575
## 454 17794 8.248 7.13 7.39 2.45 24 66.6 20.2 16.74 9.786616
## 455 14900 9.514 7.13 6.73 2.50 24 66.6 20.2 18.71 9.609117
## 456 14100 4.752 7.13 6.52 2.44 24 66.6 20.2 18.13 9.553930
## 457 12700 4.669 7.13 5.98 2.58 24 66.6 20.2 19.01 9.449357
## 458 13500 8.201 7.13 5.94 2.78 24 66.6 20.2 16.94 9.510445
## 459 14900 7.752 7.13 6.30 2.78 24 66.6 20.2 16.23 9.609117
## 460 20000 6.801 7.13 6.08 2.72 24 66.6 20.2 14.70 9.903487
## 461 16400 4.812 7.13 6.70 2.60 24 66.6 20.2 16.42 9.705036
## 462 17700 3.693 7.13 6.37 2.57 24 66.6 20.2 14.65 9.781320
## 463 19500 6.655 7.13 6.32 2.73 24 66.6 20.2 13.99 9.878170
## 464 20200 5.821 7.13 6.51 2.80 24 66.6 20.2 10.29 9.913438
## 465 21400 7.839 6.55 6.21 2.96 24 66.6 20.2 13.22 9.971147
## 466 19900 3.166 6.55 5.76 3.07 24 66.6 20.2 14.13 9.898475
## 467 19000 3.775 6.55 5.95 2.87 24 66.6 20.2 17.15 9.852194
## 468 19100 4.422 5.84 6.00 2.54 24 66.6 20.2 21.32 9.857444
## 469 17052 15.576 5.80 5.93 2.91 24 66.6 20.2 18.13 9.744022
## 470 20100 13.075 5.80 5.71 2.82 24 66.6 20.2 14.67 9.908475
## 471 19900 4.349 5.80 6.17 3.03 24 66.6 20.2 16.29 9.898475
## 472 19600 4.038 5.32 6.23 3.10 24 66.6 20.2 12.87 9.883285
## 473 23200 3.569 5.80 6.44 2.90 24 66.6 20.2 14.36 10.051908
## 474 29801 4.647 6.14 6.98 2.53 24 66.6 20.2 11.66 10.302298
## 475 13800 8.056 5.84 5.43 2.43 24 66.6 20.2 18.14 9.532424
## 476 13300 6.393 5.84 6.16 2.21 24 66.6 20.2 24.10 9.495520
## 477 16700 4.871 6.14 6.48 2.31 24 66.6 20.2 18.68 9.723164
## 478 12000 15.023 6.14 5.30 2.10 24 66.6 20.2 24.91 9.392662
## 479 14600 10.233 6.14 6.18 2.17 24 66.6 20.2 18.03 9.588777
## 480 21400 14.334 6.14 6.23 1.95 24 66.6 20.2 13.11 9.971147
## 481 23001 5.824 5.32 6.24 3.42 24 66.6 20.2 10.74 10.043293
## 482 23699 5.708 5.32 6.75 3.33 24 66.6 20.2 7.74 10.073188
## 483 24999 5.731 5.32 7.06 3.41 24 66.6 20.2 6.35 10.126591
## 484 21800 2.818 5.32 5.76 4.10 24 66.6 20.2 10.42 9.989665
## 485 20600 2.379 5.83 5.87 3.72 24 66.6 20.2 13.34 9.933046
## 486 21200 3.674 5.83 6.31 3.99 24 66.6 20.2 10.58 9.961757
## 487 19100 5.692 5.83 6.11 3.55 24 66.6 20.2 14.98 9.857444
## 488 20600 4.836 5.83 5.90 3.15 24 66.6 20.2 11.45 9.933046
## 489 15200 0.151 6.09 5.45 1.82 4 71.1 20.1 18.06 9.629050
## 490 7000 0.183 6.09 5.41 1.76 4 71.1 20.1 23.97 8.853665
## 491 8100 0.207 6.09 5.09 1.82 4 71.1 20.1 29.68 8.999619
## 492 13600 0.106 6.09 5.98 1.87 4 71.1 20.1 18.07 9.517825
## 493 20100 0.111 6.09 5.98 2.11 4 71.1 20.1 13.35 9.908475
## 494 21800 0.173 5.85 5.71 2.38 6 39.1 19.2 12.01 9.989665
## 495 24499 0.280 5.85 5.93 2.38 6 39.1 19.2 13.59 10.106387
## 496 23100 0.179 5.85 5.67 2.80 6 39.1 19.2 17.60 10.047588
## 497 19700 0.290 5.85 5.39 2.80 6 39.1 19.2 21.14 9.888374
## 498 18300 0.268 5.85 5.79 2.89 6 39.1 19.2 14.10 9.814656
## 499 21200 0.239 5.85 6.02 2.41 6 39.1 19.2 12.92 9.961757
## 500 17500 0.178 5.85 5.57 2.40 6 39.1 19.2 15.10 9.769957
## 501 16800 0.224 5.85 6.03 2.50 6 39.1 19.2 14.33 9.729135
## 502 22400 0.063 5.73 6.59 2.48 1 27.3 21.0 9.67 10.016816
## 503 20600 0.045 5.73 6.12 2.29 1 27.3 21.0 9.08 9.933046
## 504 23899 0.061 5.73 6.98 2.17 1 27.3 21.0 5.64 10.081592
## 505 22000 0.110 5.73 6.79 2.39 1 27.3 21.0 6.48 9.998797
## 506 11900 0.047 5.73 6.03 2.51 1 27.3 21.0 7.88 9.384294
## lnox lproptax
## 1 1.682688 5.690360
## 2 1.545433 5.488938
## 3 1.545433 5.488938
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## 495 1.766442 5.968708
## 496 1.766442 5.968708
## 497 1.766442 5.968708
## 498 1.766442 5.968708
## 499 1.766442 5.968708
## 500 1.766442 5.968708
## 501 1.766442 5.968708
## 502 1.745715 5.609472
## 503 1.745715 5.609472
## 504 1.745715 5.609472
## 505 1.745715 5.609472
## 506 1.745715 5.609472library(stargazer)
modelo_estimado <- lm(formula = log(price)~log(nox)+log(dist)+rooms + stratio,data=datosparcial_1)
stargazer(modelo_estimado, title = "Modelo estimado del parcial 2",type = "text")##
## Modelo estimado del parcial 2
## ===============================================
## Dependent variable:
## ---------------------------
## log(price)
## -----------------------------------------------
## log(nox) -0.954***
## (0.117)
##
## log(dist) -0.134***
## (0.043)
##
## rooms 0.255***
## (0.019)
##
## stratio -0.052***
## (0.006)
##
## Constant 11.084***
## (0.318)
##
## -----------------------------------------------
## Observations 506
## R2 0.584
## Adjusted R2 0.581
## Residual Std. Error 0.265 (df = 501)
## F Statistic 175.855*** (df = 4; 501)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01library(tseries)## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zooJB <- jarque.bera.test(modelo_estimado$residuals)
print(JB)##
## Jarque Bera Test
##
## data: modelo_estimado$residuals
## X-squared = 480.14, df = 2, p-value < 2.2e-16library(nortest)
KS <- lillie.test(modelo_estimado$residuals)
print(KS)##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: modelo_estimado$residuals
## D = 0.082888, p-value = 7.618e-09SW <- shapiro.test(modelo_estimado$residuals)
print(SW)##
## Shapiro-Wilk normality test
##
## data: modelo_estimado$residuals
## W = 0.91733, p-value = 5.123e-16matriz_x <- model.matrix(modelo_estimado)
matriz_xx <- t(matriz_x)%*%matriz_x
print(matriz_xx)## (Intercept) log(nox) log(dist) rooms stratio
## (Intercept) 506.0000 856.7042 601.2460 3179.730 9340.40
## log(nox) 856.7042 1470.9644 970.7318 5361.778 15864.36
## log(dist) 601.2460 970.7318 861.4064 3827.377 10960.02
## rooms 3179.7300 5361.7783 3827.3770 20230.874 58423.52
## stratio 9340.4001 15864.3573 10960.0198 58423.516 174785.98options(scipen = 999)
matriz_norma <- solve(diag(sqrt(diag(matriz_xx))))
print(matriz_norma)## [,1] [,2] [,3] [,4] [,5]
## [1,] 0.04445542 0.00000000 0.00000000 0.000000000 0.00000000
## [2,] 0.00000000 0.02607347 0.00000000 0.000000000 0.00000000
## [3,] 0.00000000 0.00000000 0.03407187 0.000000000 0.00000000
## [4,] 0.00000000 0.00000000 0.00000000 0.007030605 0.00000000
## [5,] 0.00000000 0.00000000 0.00000000 0.000000000 0.00239192matriz_norma_xx <- (matriz_norma %*% matriz_xx) %*% matriz_norma
print(matriz_norma_xx)## [,1] [,2] [,3] [,4] [,5]
## [1,] 1.0000000 0.9930122 0.9106949 0.9938198 0.9932005
## [2,] 0.9930122 1.0000000 0.8623710 0.9828799 0.9893913
## [3,] 0.9106949 0.8623710 1.0000000 0.9168322 0.8932109
## [4,] 0.9938198 0.9828799 0.9168322 1.0000000 0.9824876
## [5,] 0.9932005 0.9893913 0.8932109 0.9824876 1.0000000autovalor_xx <- eigen(matriz_xx, symmetric = TRUE)
print(autovalor_xx)## eigen() decomposition
## $values
## [1] 197022.6018649 676.0377359 140.6347996 15.3275059 0.6277275
##
## $vectors
## [,1] [,2] [,3] [,4] [,5]
## [1,] -0.05042542 -0.06687014 -0.01392681 0.30335472 0.949087781
## [2,] -0.08557451 -0.04241749 -0.32293427 0.89326109 -0.297784899
## [3,] -0.05935747 -0.26727095 0.91497875 0.27974642 -0.097973267
## [4,] -0.31598081 -0.90288750 -0.23594880 -0.16845505 -0.030022572
## [5,] -0.94168312 0.32724539 0.05159026 -0.05852674 -0.007511387K <- sqrt(max(autovalor_xx$values)/min(autovalor_xx$values))
print(K)## [1] 560.2379Zn <- scale(matriz_x[,-1])
print(Zn)## log(nox) log(dist) rooms stratio
## 1 -0.051650757 0.4083622534 0.406990217 -1.45870324
## 2 -0.733124891 0.7695752717 0.193495447 -0.30440644
## 3 -0.733124891 0.7695752717 1.275201241 -0.30440644
## 4 -0.850962122 1.1371185879 1.019007924 0.11114128
## 5 -0.850962122 1.1371185879 1.232502694 0.11114128
## 6 -0.850962122 1.1371185879 0.207728069 0.11114128
## 7 -0.182562442 0.9775050005 -0.390056337 -1.50487531
## 8 -0.182562442 1.1031638732 -0.162328944 -1.50487531
## 9 -0.182562442 1.1432258847 -0.930909574 -1.50487531
## 10 -0.182562442 1.2925280839 -0.404289638 -1.50487531
## 11 -0.182562442 1.2237634798 0.136563598 -1.50487531
## 12 -0.182562442 1.1884003175 -0.390056337 -1.50487531
## 13 -0.182562442 0.9404661003 -0.560852560 -1.50487531
## 14 -0.051650757 0.6699797563 -0.475454788 1.17309439
## 15 -0.051650757 0.5688879328 -0.261960018 1.17309439
## 16 -0.051650757 0.5854377111 -0.646250332 1.17309439
## 17 -0.051650757 0.5854377111 -0.503920712 1.17309439
## 18 -0.051650757 0.4838472023 -0.418522940 1.17309439
## 19 -0.051650757 0.2720437834 -1.172870268 1.17309439
## 20 -0.051650757 0.2720437834 -0.788579953 1.17309439
## 21 -0.051650757 0.2720437834 -1.016307346 1.17309439
## 22 -0.051650757 0.3717474773 -0.461221486 1.17309439
## 23 -0.051650757 0.3578281813 -0.205028170 1.17309439
## 24 -0.051650757 0.4128885528 -0.674716257 1.17309439
## 25 -0.051650757 0.5437828606 -0.518153335 1.17309439
## 26 -0.051650757 0.5647271969 -0.973608799 1.17309439
## 27 -0.051650757 0.6581357696 -0.674716257 1.17309439
## 28 -0.051650757 0.5647271969 -0.333124489 1.17309439
## 29 -0.051650757 0.5647271969 0.293125842 1.17309439
## 30 -0.051650757 0.4707476599 0.549319837 1.17309439
## 31 -0.051650757 0.4707476599 -0.845511801 1.17309439
## 32 -0.051650757 0.4442677404 -0.304658565 1.17309439
## 33 -0.051650757 0.3624795335 -0.475454788 1.17309439
## 34 -0.051650757 0.2671595569 -0.831279178 1.17309439
## 35 -0.051650757 0.2524291784 -0.261960018 1.17309439
## 36 -0.425279073 0.0439439139 -0.503920712 0.34200072
## 37 -0.425279073 0.0549444504 -0.632017031 0.34200072
## 38 -0.425279073 0.3343947107 -0.617784408 0.34200072
## 39 -0.425279073 0.2962737087 -0.446988864 0.34200072
## 40 -1.187320177 0.9233825321 0.435456141 -0.07354699
## 41 -1.187320177 0.9233825321 1.047473848 -0.07354699
## 42 -0.960568971 1.0300918722 0.691649458 -0.25823437
## 43 -0.960568971 1.0300918722 -0.162328944 -0.25823437
## 44 -0.960568971 1.0300918722 -0.105397096 -0.25823437
## 45 -0.960568971 1.0300918722 -0.304658565 -0.25823437
## 46 -0.960568971 0.8174356507 -0.859745103 -0.25823437
## 47 -0.960568971 0.8174356507 -0.703182181 -0.25823437
## 48 -0.960568971 1.0203448831 -0.361590413 -0.25823437
## 49 -0.960568971 1.0780729600 -1.258268040 -0.25823437
## 50 -0.960568971 1.1462720760 -0.973608799 -0.25823437
## 51 -1.061327821 1.3533968108 -0.461221486 -0.76612534
## 52 -1.061327821 1.3533968108 -0.247726716 -0.76612534
## 53 -1.061327821 1.3533968108 0.321592444 -0.76612534
## 54 -1.061327821 1.3533968108 -0.404289638 1.21926645
## 55 -1.400646617 1.4872579852 -0.560852560 -0.25823437
## 56 -1.486146396 1.8073920481 1.374832315 -0.53526589
## 57 -1.400646617 1.9089542051 0.136563598 -1.55104693
## 58 -1.388551345 1.7246103957 0.762814607 0.57286017
## 59 -0.905462832 1.6073589732 -0.205028170 0.57286017
## 60 -0.905462832 1.3857742784 -0.503920712 0.57286017
## 61 -0.905462832 1.3397375449 -0.774347330 0.57286017
## 62 -0.905462832 1.3561167043 -0.446988864 0.57286017
## 63 -0.905462832 1.4643269578 0.250427295 0.57286017
## 64 -0.905462832 1.6472726280 0.677416835 0.57286017
## 65 -1.328514761 1.9149952981 1.161337545 0.06496921
## 66 -1.548132371 1.2981449452 0.008466601 -1.08932804
## 67 -1.548132371 1.2981449452 -0.703182181 -1.08932804
## 68 -1.412770848 1.2670393557 -0.575085183 0.20348453
## 69 -1.412770848 1.2670393557 -0.987841422 0.20348453
## 70 -1.412770848 1.2670393557 -0.575085183 0.20348453
## 71 -1.364449412 0.8852348142 0.193495447 0.34200072
## 72 -1.364449412 0.8852348142 -0.461221486 0.34200072
## 73 -1.364449412 0.8852348142 -0.318891866 0.34200072
## 74 -1.364449412 0.8852348142 -0.062698549 0.34200072
## 75 -1.083999042 0.4794908971 -0.019999324 0.11114128
## 76 -1.083999042 0.5854377111 0.008466601 0.11114128
## 77 -1.083999042 0.3901452736 -0.005766022 0.11114128
## 78 -1.083999042 0.4083622534 -0.205028170 0.11114128
## 79 -1.083999042 0.7844337476 -0.076931172 0.11114128
## 80 -1.083999042 0.5854377111 -0.589318484 0.11114128
## 81 -1.210575434 0.9233825321 0.634717609 0.24965659
## 82 -1.210575434 0.9233825321 0.478154688 0.24965659
## 83 -1.210575434 0.9233825321 0.022699902 0.24965659
## 84 -1.210575434 0.9233825321 -0.162328944 0.24965659
## 85 -0.949499022 0.6973247915 0.150796221 0.01879714
## 86 -0.949499022 0.5605572993 0.492387989 0.01879714
## 87 -0.949499022 0.5563778002 -0.390056337 0.01879714
## 88 -0.949499022 0.2474929229 -0.233494094 0.01879714
## 89 -0.525788351 0.0767513232 1.033241226 -0.30440644
## 90 -0.525788351 0.0713236097 1.132871621 -0.30440644
## 91 -0.525788351 -0.1113289717 0.193495447 -0.30440644
## 92 -0.525788351 -0.1113289717 0.165029522 -0.30440644
## 93 -0.786340967 0.2075223640 0.221961371 -0.11971817
## 94 -0.786340967 0.2075223640 -0.105397096 -0.11971817
## 95 -0.786340967 0.1769683167 -0.048465248 -0.11971817
## 96 -0.993928748 0.1196101768 0.478154688 -0.21206231
## 97 -0.993928748 0.1196101768 -0.176562245 -0.21206231
## 98 -0.993928748 0.1196101768 2.541935882 -0.21206231
## 99 -0.993928748 0.1196101768 2.186112170 -0.21206231
## 100 -0.993928748 0.1196101768 1.616793009 -0.21206231
## 101 -0.220608519 -0.3072880940 0.634717609 1.12692232
## 102 -0.220608519 -0.2547012223 0.705882759 1.12692232
## 103 -0.220608519 -0.3545581967 0.165029522 1.12692232
## 104 -0.220608519 -0.3545581967 -0.205028170 1.12692232
## 105 -0.220608519 -0.5643466379 -0.162328944 1.12692232
## 106 -0.220608519 -0.8184326724 -0.617784408 1.12692232
## 107 -0.220608519 -0.7326040389 -0.632017031 1.12692232
## 108 -0.220608519 -0.8096687651 -0.219260792 1.12692232
## 109 -0.220608519 -0.5567030691 0.264659917 1.12692232
## 110 -0.220608519 -0.4673574438 -0.076931172 1.12692232
## 111 0.030719389 -0.3072880940 -0.133863020 1.12692232
## 112 0.030719389 -0.3751917622 0.606251685 -0.30440644
## 113 0.030719389 -0.6187529934 -0.532386636 -0.30440644
## 114 0.030719389 -0.4100998145 -0.276192640 -0.30440644
## 115 0.030719389 -0.6911355790 -0.048465248 -0.30440644
## 116 0.030719389 -0.5339596817 -0.503920712 -0.30440644
## 117 0.030719389 -0.3409289968 -0.148096321 -0.30440644
## 118 0.030719389 -0.3273992809 -0.375823714 -0.30440644
## 119 0.030719389 -0.5189509937 -0.589318484 -0.30440644
## 120 0.330118332 -0.3206712776 -0.788579953 -0.30440644
## 121 0.330118332 -0.6911355790 -0.589318484 0.29582866
## 122 0.330118332 -0.7410102339 -0.404289638 0.29582866
## 123 0.330118332 -0.8360857863 -0.461221486 0.29582866
## 124 0.330118332 -0.9741319068 -0.603551107 0.29582866
## 125 0.330118332 -0.9084291302 -0.575085183 0.29582866
## 126 0.330118332 -0.9269649132 -0.418522940 0.29582866
## 127 0.684616793 -1.1546212774 -0.959375498 0.29582866
## 128 0.684616793 -1.1232927082 -0.845511801 1.26543852
## 129 0.684616793 -1.1026973529 0.207728069 1.26543852
## 130 0.684616793 -0.9363027811 -0.916676951 1.26543852
## 131 0.684616793 -0.8096687651 0.250427295 1.26543852
## 132 0.684616793 -0.6829520652 0.065398449 1.26543852
## 133 0.684616793 -0.6345955080 0.122330297 1.26543852
## 134 0.684616793 -0.5264401467 -0.660482955 1.26543852
## 135 0.684616793 -0.6187529934 -0.745880728 1.26543852
## 136 0.684616793 -0.8184326724 0.065398449 1.26543852
## 137 0.684616793 -0.9456879294 -0.489687411 1.26543852
## 138 0.684616793 -1.0621805835 0.236193993 1.26543852
## 139 0.684616793 -1.2519152607 -0.603551107 1.26543852
## 140 0.684616793 -1.2519152607 -0.190794868 1.26543852
## 141 0.684616793 -1.3197361021 -0.162328944 1.26543852
## 142 0.684616793 -1.5265772963 -1.799121277 1.26543852
## 143 2.340400607 -1.6878585068 -1.258268040 -1.73573476
## 144 2.340400607 -1.5656012684 -1.158637645 -1.73573476
## 145 2.340400607 -1.6462036570 -1.969916821 -1.73573476
## 146 2.340400607 -1.5525018294 -0.219260792 -1.73573476
## 147 2.340400607 -1.4263603044 -0.930909574 -1.73573476
## 148 2.340400607 -1.5010105075 -1.927218274 -1.73573476
## 149 2.340400607 -1.4142057501 -1.557160582 -1.73573476
## 150 2.340400607 -1.4142057501 -0.973608799 -1.73573476
## 151 2.340400607 -1.3082588961 -0.233494094 -1.73573476
## 152 2.340400607 -1.3429059391 -1.258268040 -1.73573476
## 153 2.340400607 -1.3197361021 -1.813353899 -1.73573476
## 154 2.340400607 -1.3082588961 -0.817045877 -1.73573476
## 155 2.340400607 -1.1651829177 -0.219260792 -1.73573476
## 156 2.340400607 -1.1651829177 -0.190794868 -1.73573476
## 157 2.340400607 -1.1758050835 -1.443296886 -1.73573476
## 158 0.531090054 -1.0323639162 0.933610152 -1.73573476
## 159 0.531090054 -1.1546212774 -0.304658565 -1.73573476
## 160 2.340400607 -1.1441194767 0.321592444 -1.73573476
## 161 0.531090054 -1.1129664258 -0.048465248 -1.73573476
## 162 0.531090054 -0.9456879294 1.716423404 -1.73573476
## 163 0.531090054 -0.8809684371 2.157646246 -1.73573476
## 164 0.531090054 -0.7750215148 2.968925422 -1.73573476
## 165 0.531090054 -0.5643466379 -0.617784408 -1.73573476
## 166 0.531090054 -0.6748045229 -0.261960018 -1.73573476
## 167 0.531090054 -0.8719045418 2.342674413 -1.73573476
## 168 0.531090054 -0.5567030691 -0.575085183 -1.73573476
## 169 0.531090054 -0.8272382137 0.051165826 -1.73573476
## 170 0.531090054 -0.6911355790 0.165029522 -1.73573476
## 171 0.531090054 -0.5567030691 -0.589318484 -1.73573476
## 172 0.531090054 -0.5874683030 -0.575085183 -1.73573476
## 173 -0.317019096 -0.4313648001 -1.016307346 -0.85846859
## 174 -0.317019096 -0.3960576050 0.193495447 -0.85846859
## 175 -0.317019096 -0.3614105625 -0.603551107 -0.85846859
## 176 -0.317019096 -0.0874884643 0.378524293 -0.85846859
## 177 -0.317019096 0.1459022896 -0.375823714 -0.85846859
## 178 -0.317019096 0.0105454806 0.036932525 -0.85846859
## 179 -0.317019096 -0.2225761253 0.819746455 -0.85846859
## 180 -0.535951856 -0.2742468824 0.990542000 -0.30440644
## 181 -0.535951856 -0.3341517942 2.100714397 -0.30440644
## 182 -0.535951856 -0.4313648001 -0.205028170 -0.30440644
## 183 -0.535951856 -0.3614105625 1.232502694 -0.30440644
## 184 -0.535951856 -0.2611935685 0.392756915 -0.30440644
## 185 -0.535951856 -0.1723069338 -0.973608799 -0.30440644
## 186 -0.535951856 -0.0007224135 -0.190794868 -0.30440644
## 187 -0.535951856 -0.0464917230 2.200344792 -0.30440644
## 188 -1.083999042 0.2671595569 0.705882759 -1.50487531
## 189 -1.083999042 0.6140490486 0.392756915 -1.50487531
## 190 -1.083999042 0.6140490486 1.275201241 -1.50487531
## 191 -1.083999042 1.2613272930 0.947842775 -1.50487531
## 192 -1.083999042 1.2613272930 0.648950232 -1.50487531
## 193 -1.083999042 1.2613272930 1.275201241 -1.50487531
## 194 -1.510847881 1.1854226348 0.734348683 -1.32018748
## 195 -1.510847881 1.1854226348 0.449688763 -1.32018748
## 196 -1.257415855 1.0072685479 2.257276641 -1.87425051
## 197 -1.473841879 1.4847240039 1.431764163 -2.70534418
## 198 -1.473841879 1.4847240039 1.175570846 -2.70534418
## 199 -1.473841879 1.4847240039 1.403298239 -2.70534418
## 200 -1.486146396 1.5689914900 0.976308699 -0.67378120
## 201 -1.486146396 1.5689914900 1.204036770 -0.67378120
## 202 -1.340463913 1.2002631603 -0.176562245 -1.73573476
## 203 -1.340463913 1.2002631603 1.887219627 -1.73573476
## 204 -1.328514761 0.8246903093 2.228810716 -1.73573476
## 205 -1.328514761 0.8246903093 2.485004033 -1.73573476
## 206 -0.525788351 0.3438036793 -0.560852560 0.06496921
## 207 -0.525788351 0.5225989535 0.065398449 0.06496921
## 208 -0.525788351 0.5225989535 -0.717414803 0.06496921
## 209 -0.525788351 0.4751243295 -0.318891866 0.06496921
## 210 -0.525788351 0.3058776831 -1.343665812 0.06496921
## 211 -0.525788351 0.3106611878 -0.461221486 0.06496921
## 212 -0.525788351 0.2075223640 -1.258268040 0.06496921
## 213 -0.525788351 0.1973935803 -0.674716257 0.06496921
## 214 -0.525788351 0.3438036793 0.122330297 0.06496921
## 215 -0.525788351 0.1666707185 -1.244035417 0.06496921
## 216 -0.525788351 0.3438036793 -0.148096321 0.06496921
## 217 0.057875491 -0.0993704598 -0.560852560 -0.95081272
## 218 0.057875491 0.0767513232 0.506620612 -0.95081272
## 219 0.057875491 -0.2353593676 -0.475454788 -0.95081272
## 220 0.057875491 0.0439439139 0.122330297 -0.95081272
## 221 -0.346310916 -0.2547012223 0.947842775 -0.95081272
## 222 -0.346310916 -0.1354799700 -0.176562245 -0.48909382
## 223 -0.346310916 -0.0063821519 0.848212380 -0.48909382
## 224 -0.346310916 -0.0063821519 0.478154688 -0.48909382
## 225 -0.375777044 -0.2353593676 2.826596480 -0.48909382
## 226 -0.375777044 -0.2353593676 3.467080112 -0.48909382
## 227 -0.375777044 -0.0349430075 2.499237335 -0.48909382
## 228 -0.375777044 -0.0349430075 1.246735317 -0.48909382
## 229 -0.375777044 0.0549444504 2.001083324 -0.48909382
## 230 -0.375777044 0.0549444504 0.378524293 -0.48909382
## 231 -0.375777044 0.2075223640 -0.432755562 -0.48909382
## 232 -0.375777044 0.2075223640 1.602559708 -0.48909382
## 233 -0.346310916 0.2914529962 2.926226875 -0.48909382
## 234 -0.346310916 0.1973935803 2.798129877 -0.48909382
## 235 -0.346310916 0.1973935803 0.634717609 -0.48909382
## 236 -0.346310916 0.1973935803 -0.276192640 -0.48909382
## 237 -0.346310916 0.4353563636 0.492387989 -0.48909382
## 238 -0.346310916 0.4353563636 1.531395237 -0.48909382
## 239 -1.187320177 1.1764610630 0.278893219 -0.85846859
## 240 -1.187320177 1.1764610630 0.463922065 -0.85846859
## 241 -1.187320177 1.2208422520 0.876678304 -0.85846859
## 242 -1.187320177 1.2208422520 -0.276192640 -0.85846859
## 243 -1.187320177 1.4149649117 0.108097674 -0.85846859
## 244 -1.187320177 1.4149649117 0.150796221 -0.85846859
## 245 -1.152640532 1.6402911598 -0.987841422 0.29582866
## 246 -1.152640532 1.6402911598 -0.973608799 0.29582866
## 247 -1.152640532 1.6657622961 -0.247726716 0.29582866
## 248 -1.152640532 1.6657622961 -0.076931172 0.29582866
## 249 -1.152640532 1.6120995458 0.207728069 0.29582866
## 250 -1.152640532 1.6120995458 0.620484308 0.29582866
## 251 -1.152640532 1.5074056056 0.293125842 0.29582866
## 252 -1.152640532 1.5074056056 0.221961371 0.29582866
## 253 -1.152640532 1.8516018269 0.962076076 0.29582866
## 254 -1.152640532 1.8516018269 2.812363179 0.29582866
## 255 -1.623551369 1.9149952981 -0.247726716 -0.95081272
## 256 -1.623551369 1.9149952981 -0.575085183 -0.95081272
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## 483 -0.107333454 0.0713236097 1.104405696 0.80371962
## 484 -0.107333454 0.4128885528 -0.745880728 0.80371962
## 485 0.347180165 0.2326047878 -0.589318484 0.80371962
## 486 0.347180165 0.3624795335 0.036932525 0.80371962
## 487 0.347180165 0.1459022896 -0.247726716 0.80371962
## 488 0.347180165 -0.0756822919 -0.546619259 0.80371962
## 489 0.563808383 -1.0924847378 -1.187103569 0.75754756
## 490 0.563808383 -1.1546212774 -1.244035417 0.75754756
## 491 0.563808383 -1.0924847378 -1.699490203 0.75754756
## 492 0.563808383 -1.0422496082 -0.432755562 0.75754756
## 493 0.563808383 -0.8184326724 -0.432755562 0.75754756
## 494 0.364183568 -0.5952400661 -0.817045877 0.34200072
## 495 0.364183568 -0.5952400661 -0.503920712 0.34200072
## 496 0.364183568 -0.2940008480 -0.873977725 0.34200072
## 497 0.364183568 -0.2940008480 -1.272501341 0.34200072
## 498 0.364183568 -0.2353593676 -0.703182181 0.34200072
## 499 0.364183568 -0.5720218571 -0.375823714 0.34200072
## 500 0.364183568 -0.5797289900 -1.016307346 0.34200072
## 501 0.364183568 -0.5040628586 -0.361590413 0.34200072
## 502 0.261278566 -0.5189509937 0.435456141 1.17309439
## 503 0.261278566 -0.6666926374 -0.233494094 1.17309439
## 504 0.261278566 -0.7664600086 0.990542000 1.17309439
## 505 0.261278566 -0.5874683030 0.720115382 1.17309439
## 506 0.261278566 -0.4966633963 -0.361590413 1.17309439
## attr(,"scaled:center")
## log(nox) log(dist) rooms stratio
## 1.693091 1.188233 6.284051 18.459289
## attr(,"scaled:scale")
## log(nox) log(dist) rooms stratio
## 0.2014101 0.5395010 0.7025938 2.1658199n_R <- nrow(Zn)
matriz_R <- (t(Zn)%*%Zn)*(1/(n_R-1))
print(matriz_R)## log(nox) log(dist) rooms stratio
## log(nox) 1.0000000 -0.8607498 -0.3049879 0.2279104
## log(dist) -0.8607498 1.0000000 0.2565893 -0.2348069
## rooms -0.3049879 0.2565893 1.0000000 -0.3540075
## stratio 0.2279104 -0.2348069 -0.3540075 1.0000000determi_R <- det(matriz_R)
print(determi_R)## [1] 0.2003115m_FG <- ncol(matriz_x[,-1])
n_R <- nrow(matriz_x[,-1])
chi_FG <- -(n_R-1-(2*m_FG+5)/6)*log(determi_R)
print(chi_FG)## [1] 808.4964gl_FG <- m_FG*(m_FG-1)/2
vc_FG <- qchisq(p = 0.95, df = gl_FG)
print(vc_FG)## [1] 12.59159library(car)## Loading required package: carDataVIF_car <- vif(modelo_estimado)
print(VIF_car)## log(nox) log(dist) rooms stratio
## 3.975625 3.888603 1.218893 1.173037