Including Plots
g1=ggplot(aquifer, aes(Profundidad, Este)) +
geom_point() +
geom_line() +
xlab("Este") +
ylab("Profundidad")
g2=ggplot(aquifer, aes(Profundidad, Norte)) +
geom_point() +
geom_line() +
xlab("Norte") +
ylab("Profundidad")
g3=ggplot(aquifer, aes(Profundidad, Este*Norte)) +
geom_point() +
geom_line() +
xlab("Interacción este,norte") +
ylab("Profundidad")
g3=ggplot(aquifer, aes(Profundidad, Este*Norte)) +
geom_point() +
geom_line() +
xlab("Interacción este,norte") +
ylab("Profundidad")
plot_grid(g1,g2,g3)
cor(aquifer)
## Este Norte Profundidad
## Este 1.0000000 0.1147565 -0.7788885
## Norte 0.1147565 1.0000000 -0.6200923
## Profundidad -0.7788885 -0.6200923 1.0000000
scatterplot3d(aquifer, highlight.3d=TRUE, col.axis="blue",
col.grid="lightblue", main="Tendencia de Profundidad", pch=20)
reg1 <- lm(Profundidad ~ Este + Norte, data = aquifer)
residuales1 <- residuals(reg1)
summary(reg1)
##
## Call:
## lm(formula = Profundidad ~ Este + Norte, data = aquifer)
##
## Residuals:
## Min 1Q Median 3Q Max
## -366.96 -161.53 -30.71 148.15 651.20
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2591.4302 38.9599 66.52 <2e-16 ***
## Este -6.7514 0.3438 -19.64 <2e-16 ***
## Norte -5.9872 0.4066 -14.73 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 203.3 on 82 degrees of freedom
## Multiple R-squared: 0.8921, Adjusted R-squared: 0.8894
## F-statistic: 338.9 on 2 and 82 DF, p-value: < 2.2e-16
anova(reg1)
## Analysis of Variance Table
##
## Response: Profundidad
## Df Sum Sq Mean Sq F value Pr(>F)
## Este 1 19045642 19045642 460.95 < 2.2e-16 ***
## Norte 1 8960172 8960172 216.86 < 2.2e-16 ***
## Residuals 82 3388069 41318
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
reg2 <- lm(Profundidad ~ Este*Norte, data = aquifer)
residuales2 <- residuals(reg2)
summary(reg2)
##
## Call:
## lm(formula = Profundidad ~ Este * Norte, data = aquifer)
##
## Residuals:
## Min 1Q Median 3Q Max
## -406.30 -138.88 -13.04 129.36 722.48
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.627e+03 3.833e+01 68.546 < 2e-16 ***
## Este -8.287e+00 5.658e-01 -14.646 < 2e-16 ***
## Norte -6.649e+00 4.327e-01 -15.366 < 2e-16 ***
## Este:Norte 2.452e-02 7.401e-03 3.314 0.00138 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 191.9 on 81 degrees of freedom
## Multiple R-squared: 0.905, Adjusted R-squared: 0.9014
## F-statistic: 257.1 on 3 and 81 DF, p-value: < 2.2e-16
anova(reg2)
## Analysis of Variance Table
##
## Response: Profundidad
## Df Sum Sq Mean Sq F value Pr(>F)
## Este 1 19045642 19045642 517.06 < 2.2e-16 ***
## Norte 1 8960172 8960172 243.25 < 2.2e-16 ***
## Este:Norte 1 404448 404448 10.98 0.001379 **
## Residuals 81 2983621 36835
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
reg3 <- lm(Profundidad ~ Este*Norte+I(Este^2)*I(Norte^2), data = aquifer)
residuales3 <- residuals(reg3)
summary(reg3)
##
## Call:
## lm(formula = Profundidad ~ Este * Norte + I(Este^2) * I(Norte^2),
## data = aquifer)
##
## Residuals:
## Min 1Q Median 3Q Max
## -372.7 -133.6 -20.3 129.9 505.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.538e+03 7.038e+01 36.055 <2e-16 ***
## Este -7.728e+00 6.028e-01 -12.822 <2e-16 ***
## Norte -3.075e+00 1.770e+00 -1.737 0.0863 .
## I(Este^2) -6.792e-03 5.967e-03 -1.138 0.2585
## I(Norte^2) -2.372e-02 9.049e-03 -2.622 0.0105 *
## Este:Norte 1.155e-02 9.680e-03 1.193 0.2365
## I(Este^2):I(Norte^2) 2.251e-06 9.541e-07 2.360 0.0208 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 180.7 on 78 degrees of freedom
## Multiple R-squared: 0.9189, Adjusted R-squared: 0.9126
## F-statistic: 147.2 on 6 and 78 DF, p-value: < 2.2e-16
anova(reg3)
## Analysis of Variance Table
##
## Response: Profundidad
## Df Sum Sq Mean Sq F value Pr(>F)
## Este 1 19045642 19045642 583.2335 < 2.2e-16 ***
## Norte 1 8960172 8960172 274.3868 < 2.2e-16 ***
## I(Este^2) 1 55368 55368 1.6955 0.1967061
## I(Norte^2) 1 152170 152170 4.6599 0.0339500 *
## Este:Norte 1 451567 451567 13.8283 0.0003755 ***
## I(Este^2):I(Norte^2) 1 181854 181854 5.5689 0.0207829 *
## Residuals 78 2547110 32655
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
aquifer=data.frame(aquifer,resi=residuales2)
aquifer_points=point(aquifer, x="Este", y="Norte")
aquifer_pair=pair(aquifer_points,,num.lags=10)
## ....................................................................................
aquifer_pair$bins
## [1] 13.55308 40.65923 67.76539 94.87154 121.97770 149.08385 176.19001
## [8] 203.29616 230.40231 257.50847
aquifer_pair$dist
## [1] 79.2593133 61.2927436 79.9283065 82.8019360 79.5299809 84.5144082
## [7] 100.2085578 107.1520083 89.9783035 104.1785410 99.2510576 88.8997176
## [13] 87.9450514 70.1659872 101.6742104 112.8721648 120.9613079 119.0479060
## [19] 32.7546337 46.1569203 27.6896467 74.0103755 65.7292774 107.8859461
## [25] 23.2298281 87.3555316 98.8808622 107.5814605 104.1008788 104.1504384
## [31] 52.2851327 71.5833717 76.0112193 87.0333421 51.1947513 129.8052624
## [37] 135.5551366 122.8514650 125.3405455 49.2197721 119.7078074 119.9051079
## [43] 123.1557730 112.0018224 114.9164083 115.4601984 103.8292559 104.1798969
## [49] 113.2504713 96.5435190 97.5662872 96.7002581 82.7814952 63.1565458
## [55] 64.2183216 65.8354765 24.5676156 35.1069244 54.8325215 45.8091863
## [61] 40.3302803 56.1105548 43.9356951 46.5192162 45.7131772 50.4315630
## [67] 50.8015119 61.1248068 55.9028462 44.6047036 62.4495436 185.8524317
## [73] 212.7705615 123.3237129 143.2560523 141.1356104 169.6416077 148.1832290
## [79] 143.1877052 166.1767438 149.4170564 150.2519410 166.0777066 163.2085761
## [85] 26.8873847 16.8097266 126.6044524 136.1865843 120.7447679 128.2465529
## [91] 133.6773833 129.6834923 130.5118433 129.5851654 130.7696492 94.0379994
## [97] 23.3256506 105.3079496 123.5224481 133.0497595 131.8534947 97.7230762
## [103] 103.9266182 93.9280588 79.9593580 72.4409726 147.3195921 99.6011936
## [109] 54.1018186 55.6329165 65.8730346 62.2256499 62.4215776 91.3215244
## [115] 85.9480431 81.5641567 68.6568038 129.9548287 75.9680821 81.4631040
## [121] 69.0797198 74.3157117 101.9670041 145.1282667 145.4707669 148.4430852
## [127] 60.9434255 61.3098442 61.9531843 55.4778792 53.8750660 81.9573509
## [133] 106.2165676 112.4762888 109.9583251 60.8357496 47.6471372 41.4888353
## [139] 46.6221840 68.6026477 50.3023781 25.5363793 116.4047820 113.6012622
## [145] 129.4675978 121.0216648 123.6656592 117.7738613 122.2443828 123.3298729
## [151] 35.0353117 47.5693087 123.2564912 138.7454566 109.2440817 133.5121599
## [157] 46.6811504 67.2138470 63.0447052 93.4013595 69.0210498 65.8441336
## [163] 87.1193059 71.7112919 71.6234788 87.6078339 85.9550742 19.3904667
## [169] 99.7196915 109.7430526 93.9359473 101.9860994 107.6397974 102.8358862
## [175] 104.4380247 103.1696116 103.8915231 102.4631993 38.3589598 81.6642162
## [181] 99.3167644 108.8815930 107.5352105 73.6451017 78.3520295 70.4047502
## [187] 54.4430626 46.2992483 120.5688925 83.8510477 37.2888028 44.5698629
## [193] 54.9952344 51.0900484 51.2242064 64.6129451 90.7284518 88.8279912
## [199] 82.5926106 112.3225761 72.8551855 78.7356698 65.6000155 69.3849095
## [205] 95.4322643 119.3895442 119.7217632 122.7705740 55.2186707 57.2865259
## [211] 57.9026933 47.5583720 47.0881510 67.3932029 81.5421592 87.2602498
## [217] 84.8859773 74.9540067 55.9934648 51.0665203 56.3780900 58.7656408
## [223] 42.8645368 23.9778242 103.9637324 99.8207261 115.9629295 105.0875573
## [229] 107.6991341 104.6917424 109.3931023 110.1478361 8.9355703 20.8103421
## [235] 102.7591223 116.2264345 124.9340602 154.8925990 72.8951983 93.3349656
## [241] 88.0682208 119.1677182 90.1872661 82.9345749 107.5495626 89.3061405
## [247] 91.0203855 106.4414364 102.6848662 115.6943948 127.3451903 108.8349383
## [253] 114.8496924 119.9174843 117.9668867 116.8184895 116.4603831 119.3676331
## [259] 108.4513561 38.3522809 89.8333914 108.2376359 117.6999989 116.5951923
## [265] 92.8964671 97.0061660 89.7466538 66.0860347 59.4788666 135.0074501
## [271] 102.0022720 37.4639752 38.9725866 49.3417474 45.6262792 45.8169067
## [277] 81.8992196 98.9724480 95.4656796 84.4677581 131.1068938 61.5089578
## [283] 67.2198141 54.3798474 59.2292765 109.9629369 130.9496647 131.3022063
## [289] 134.1794085 45.3913863 46.2733388 46.9222092 39.2893894 37.8949742
## [295] 65.1770650 91.3351667 97.9653982 95.3459937 76.6158039 61.3391429
## [301] 55.4382308 60.8001598 74.3396578 56.8378397 32.9704654 121.0922178
## [307] 117.4124709 133.5342149 123.3973834 126.0281776 122.0607268 126.7017579
## [313] 127.5796742 24.3880902 36.8776001 122.0449373 135.6078638 105.9378983
## [319] 135.5637545 56.5606428 76.5427723 70.2320736 101.7322113 70.9332016
## [325] 63.6204738 88.1879461 69.9688830 71.6327455 87.0606709 83.4675403
## [331] 21.9724714 11.4756710 26.1243657 31.6935766 8.3803675 30.0706461
## [337] 23.1611154 6.2091400 170.2140092 132.1471563 55.1246639 51.3539131
## [343] 54.4308987 52.5342994 51.2732361 37.2752731 55.8869120 54.1899846
## [349] 57.4458793 25.0841642 93.3282810 91.7839379 103.1435497 104.6082076
## [355] 103.5038133 103.3799138 36.4354835 154.0091309 157.6413974 164.5082971
## [361] 95.4688674 128.2303306 132.1004225 124.0796631 122.5944666 129.0382369
## [367] 41.8398398 41.8960694 44.7578797 115.6774343 119.6514503 119.8271872
## [373] 109.5897130 111.5748011 96.4071879 47.0085408 40.8633325 42.7079436
## [379] 158.6646744 137.1808192 135.6100545 139.2274996 106.0667682 108.4341735
## [385] 113.3511951 113.8514923 106.7578334 115.9743653 100.1192801 101.1674277
## [391] 111.7585152 115.0452745 114.1357149 91.9894847 79.2603390 76.0044145
## [397] 67.9986561 205.3175097 244.4510254 172.0561897 192.2157080 185.7118426
## [403] 217.3279239 182.7758273 170.6150693 197.8309330 176.9036367 181.0606547
## [409] 194.2230646 187.3543598 33.2962922 47.4303500 52.1855861 28.8072391
## [415] 51.0921352 44.1741390 25.4382379 167.2205175 138.1824318 76.6682607
## [421] 73.2344600 75.7876143 73.9481947 46.8568650 34.7176036 51.9583325
## [427] 71.4532254 72.5671626 37.6155538 84.6193529 108.1149369 120.1424728
## [433] 122.8225023 121.3066583 121.2045829 45.4672595 150.8022422 155.5288329
## [439] 165.4283647 80.3201124 146.9867778 151.1988548 142.3296200 141.3663268
## [445] 121.1959380 60.4309208 60.3981688 62.8045664 133.2904413 137.2364034
## [451] 137.4750976 126.6317566 128.4299275 116.2363349 68.5151807 62.7054897
## [457] 64.4259052 160.3457662 139.3655709 138.7628557 141.7047153 103.9974894
## [463] 110.0218015 119.5076370 102.4359547 95.4939034 102.2978076 87.0285251
## [469] 87.6078330 99.9597425 102.6157123 101.4461718 103.0068197 90.4842648
## [475] 61.3198959 49.2321303 222.2824774 259.6688630 182.6253800 203.0780103
## [481] 197.5100149 228.8315895 196.6716994 185.6759872 212.5387873 192.0690185
## [487] 195.6720244 209.5414616 203.2916400 17.2770151 23.8841346 9.2490783
## [493] 21.4915730 15.2862868 11.4503447 170.6016557 128.1156457 43.6569039
## [499] 40.5772000 44.5790138 42.6188327 54.9094646 41.3108046 59.0012638
## [505] 45.0564892 49.5967664 26.7637153 97.5240428 82.6320407 93.5550964
## [511] 94.4022632 93.5059304 93.3717576 34.1041120 154.6265137 157.6590036
## [517] 162.8909517 102.7946624 117.6980589 121.4107919 113.7885134 112.0684928
## [523] 132.2910919 35.7513373 35.8997053 39.0653426 105.7187149 109.6907660
## [529] 109.8353957 99.9428229 102.0119103 85.4787264 35.5509702 29.4221072
## [535] 31.2336868 156.6920638 135.1303688 133.0660262 137.0031842 106.6550033
## [541] 107.0654223 109.4722705 119.0952427 112.0122742 122.3418001 106.3708482
## [547] 107.6378514 117.2199911 120.7890568 120.0207995 85.7765600 73.1757825
## [553] 83.4064574 77.4041665 195.4488959 235.3237773 165.3878956 185.3181523
## [559] 178.3673416 210.0342994 174.4006253 161.7074756 189.0239007 167.9281111
## [565] 172.3415798 185.1333788 177.9875187 6.9452457 18.6276904 4.2176050
## [571] 3.5388549 22.0285624 184.9151659 138.1227299 35.9721382 26.5391573
## [577] 28.3790032 26.5220295 71.7219800 58.3528712 75.5977154 48.8049760
## [583] 55.8074809 23.6153085 114.3069084 84.3988315 93.8538205 92.7448831
## [589] 92.5637863 92.3994379 48.3584365 169.1788145 171.7151923 175.4095230
## [595] 120.0556741 114.4396787 117.4612025 111.4845514 108.9141530 148.5832510
## [601] 19.5774461 19.8025965 23.0799744 104.6585087 108.5567551 108.6000185
## [607] 99.9362921 102.2055963 81.0272083 29.0444374 21.1764383 23.9204457
## [613] 168.8761999 147.3702808 144.7939734 149.0464100 121.4383414 120.2202006
## [619] 119.8846787 136.1501364 129.0785552 139.5898272 123.6139200 124.8991923
## [625] 134.3276964 137.9503331 137.2071829 93.3394946 81.2936931 100.6530309
## [631] 93.9839018 193.8078254 235.5467573 171.1159520 190.5066988 182.7702490
## [637] 214.3580156 176.7134334 162.8782294 190.2506863 168.8847547 173.8838273
## [643] 185.6905393 177.8707346 23.6407098 3.2498055 8.7159445 26.8529873
## [649] 191.7303231 144.1552982 37.4132929 24.6244564 24.1756435 22.5292147
## [655] 78.5785757 65.1321664 82.4953502 53.8537889 61.3495348 23.2677154
## [661] 121.1793856 88.3698291 97.2552089 95.4551327 95.5374949 95.3636286
## [667] 55.2598203 176.0269203 178.4989737 181.9365563 126.4552896 116.3807508
## [673] 119.1076480 113.8151779 110.9305364 155.5198928 12.7109860 12.9569067
## [679] 16.2351445 107.4983752 111.3443441 111.3500445 103.1860850 105.5097798
## [685] 82.7642842 31.4816603 23.6056440 26.4650797 175.3429137 153.8638013
## [691] 151.1900089 155.5007215 128.3232235 126.8964570 126.0400520 142.9356590
## [697] 135.8579634 146.2069965 130.2410218 131.4873467 141.0843713 144.6698247
## [703] 143.9047617 98.9084724 87.0588884 107.0205322 99.6865682 196.0998766
## [709] 238.4623955 175.9544786 195.1504457 187.1834438 218.6983577 180.4592547
## [715] 166.2666839 193.5966569 172.1831642 177.3737211 188.8095222 180.7646650
## [721] 22.3173072 15.3820031 3.4378851 176.9595304 136.5122231 50.7399463
## [727] 44.7477686 46.9816305 45.1412000 58.9883985 45.0246074 63.4633607
## [733] 54.2798268 58.8120415 18.6011186 101.2874651 91.8238680 102.6505517
## [739] 103.2646543 102.4643972 102.3261131 41.4925464 160.8414219 164.2184446
## [745] 170.3010152 103.8492032 126.3384998 129.9222612 122.5872358 120.7186036
## [751] 136.7810632 33.4643630 33.5181403 36.3787378 114.6827912 118.6511733
## [757] 118.7829309 109.0177401 111.1087314 93.7958028 42.8311792 35.9265400
## [763] 38.1245408 164.2654156 142.7236117 140.8779888 144.6770251 112.8402008
## [769] 114.3034361 117.7965299 122.0442369 114.9482898 124.3139027 108.4430274
## [775] 109.5114560 119.9857733 123.3152274 122.4236775 94.7695513 82.1239396
## [781] 84.3846815 76.1199130 204.4112568 244.4857836 174.5063691 194.4751902
## [787] 187.5768237 219.2416180 183.6455203 170.9114319 198.2367714 177.1221558
## [793] 181.5648905 194.3074777 187.1075561 6.9423807 25.6548229 188.5759245
## [799] 140.9148859 35.3239765 23.9140202 24.7405599 22.9545540 75.8884279
## [805] 62.5522594 79.7312375 50.7388323 58.1556139 24.5207856 118.4597329
## [811] 85.5293790 94.5840420 93.0038402 92.9997885 92.8289119 52.1915955
## [817] 172.8944512 175.3284661 178.6998406 124.2595111 114.2067927 117.0430936
## [823] 111.5015890 108.7271690 152.6444819 15.8840705 16.1432703 19.4148249
## [829] 105.0095575 108.8742737 108.8924606 100.5640818 102.8717534 80.6463170
## [835] 29.0167166 21.0889732 23.9350072 172.1001231 150.6237394 147.9428452
## [841] 152.2571466 125.2250804 123.6890401 122.7925853 140.3440618 133.2744477
## [847] 143.8071456 127.8310191 129.1167807 138.5293244 142.1590447 141.4189516
## [853] 95.7178234 83.8410328 104.8518240 98.0206181 193.8181363 235.9715881
## [859] 172.9105436 192.1536054 184.2436545 215.7797146 177.7031731 163.6166386
## [865] 190.9632448 169.5620234 174.6939658 186.2475406 178.2750556 18.7370508
## [871] 184.5351914 138.9250183 39.2167105 30.0644392 31.6207896 29.8013764
## [877] 70.1515968 56.5956208 74.1695018 50.5671708 57.1791509 20.6044363
## [883] 112.7684111 86.6703825 96.3667368 95.5199593 95.2452821 95.0846229
## [889] 47.8014327 168.7083836 171.4185630 175.5900617 117.7396583 117.4368531
## [895] 120.5360781 114.3680160 111.8934820 147.3555891 20.5527398 20.7230732
## [901] 23.9409595 107.3766794 111.2902716 111.3467140 102.5040821 104.7492929
## [907] 84.1063861 32.0924361 24.3083466 26.9882693 169.1474305 147.6120111
## [913] 145.1726411 149.3434944 120.8588411 120.1751158 120.5694804 134.3810342
## [919] 127.2975350 137.5329330 121.5723298 122.8033836 132.5001002 136.0537069
## [925] 135.2732156 94.6041713 82.4102136 98.3045947 91.1439633 196.6701439
## [931] 238.1851621 172.8404028 192.3422182 184.7400275 216.3579208 179.0218936
## [937] 165.3490180 192.7297497 171.3905385 176.3073137 188.2626637 180.5310089
## [943] 176.1928741 137.0378721 53.9550442 48.1856385 50.3555417 48.5257178
## [949] 57.4723192 43.4749347 62.0675796 56.3665832 60.4789972 19.0398069
## [955] 99.5328812 93.9840235 104.9832027 105.8415360 104.9560886 104.8217818
## [961] 41.5809054 160.0151831 163.5599356 170.1096851 101.2852843 129.0717608
## [967] 132.7283963 125.2145828 123.4454900 135.2441170 36.2078505 36.2390038
## [973] 38.9987218 117.1690361 121.1410498 121.2853024 111.3780786 113.4387398
## [979] 96.6884921 45.9961457 39.2079332 41.3527163 164.1785576 142.6633543
## [985] 140.9619994 144.6669760 112.0458070 114.0559453 118.2769896 119.9926932
## [991] 112.9008913 121.9707507 106.1456695 107.1569852 117.8796193 121.1329698
## [997] 120.2058210 95.9553384 83.2636543 81.8314682 73.0877762 206.8992213
## [1003] 246.6990437 175.8598251 195.9070034 189.1558915 220.8086481 185.5764453
## [1009] 173.0283952 200.3245903 179.2656004 183.6170682 196.4971844 189.3982793
## [1015] 70.7197266 177.1823454 192.2171786 201.2992849 199.5706797 120.6618932
## [1021] 134.0675769 115.6211881 147.4858451 138.0556605 195.2326161 86.6029605
## [1027] 139.7408669 145.7769723 156.3873155 152.4989628 152.6601886 136.7516396
## [1033] 16.4247297 13.8166207 29.9843743 110.2381999 169.7559607 175.3526711
## [1039] 162.7217275 167.6753331 54.8286013 204.4412577 204.6848893 207.9642049
## [1045] 153.8106718 154.6989916 155.3477818 147.3055692 146.1411864 169.8328436
## [1051] 174.3646763 177.6455766 176.0498298 36.1161565 47.1989030 53.0133325
## [1057] 47.6600952 64.1483473 66.0601570 78.5809836 81.8953664 85.4929388
## [1063] 93.3396426 97.8064428 99.4825983 85.0036685 86.5747031 88.4438094
## [1069] 109.7717042 115.4115131 118.6033408 139.4958052 190.6149812 198.1169560
## [1075] 108.9109138 120.7878446 125.9879139 141.6655443 144.3732311 149.8184373
## [1081] 160.9924458 154.0119378 150.5695129 165.2384845 167.8440598 119.9522917
## [1087] 137.4151393 146.9690192 145.5673456 95.1102192 104.0451630 90.5990331
## [1093] 92.0869070 83.3983021 154.8551208 87.1224908 73.2064674 76.9593225
## [1099] 87.4728567 83.6813558 83.8627147 95.7478994 62.9231876 58.2731189
## [1105] 46.1810169 118.1313651 99.1408625 104.6901932 92.1743324 97.2773426
## [1111] 82.8267099 156.2759023 156.5929035 159.7240712 83.6391004 84.2674137
## [1117] 84.9145388 77.6336647 76.2416823 102.5319224 119.5079950 124.8601120
## [1123] 122.6042490 38.3321222 24.5872419 18.3790511 23.3571212 53.5087182
## [1129] 36.0801618 18.8158646 100.6058782 98.9109976 114.1136229 107.8894906
## [1135] 110.4834257 102.4121432 106.5828933 107.8870666 47.2056655 57.5241780
## [1141] 114.6776723 132.3630356 128.0968140 146.9939528 54.5768343 73.7196598
## [1147] 73.0639385 99.9122766 84.6218738 84.9826593 102.7542757 90.2828813
## [1153] 88.8068797 104.6959946 104.6533390 18.5575195 27.8926713 26.8935490
## [1159] 81.8948532 72.0135535 83.9479353 29.7052166 39.1327593 59.5387712
## [1165] 120.9884644 54.5529892 61.5934392 58.5890738 59.0531737 58.8653418
## [1171] 53.1071621 162.7243481 163.4322268 162.2877104 134.9683576 78.9709083
## [1177] 81.7241836 76.5392904 73.5332620 150.6072050 44.8047238 45.1842974
## [1183] 47.4360887 70.7272201 74.4874926 74.4483327 67.1237837 69.5316286
## [1189] 45.3527590 8.1558669 15.0115973 12.6197404 155.0128042 134.3757837
## [1195] 130.5308052 135.4541407 117.7754219 111.1719771 103.5566881 144.4168067
## [1201] 137.7272730 150.9343930 135.3255756 137.1646975 143.2971414 147.5595854
## [1207] 147.2538314 72.7631608 63.2536149 116.7342206 115.9518344 158.7496605
## [1213] 201.5183860 143.8988322 162.1790225 153.4548568 184.5872484 144.9386493
## [1219] 130.0875528 157.2733044 135.8344234 141.3425460 152.1598669 143.8557235
## [1225] 9.5655533 8.3601145 88.9920123 77.1855849 91.9160902 45.6627273
## [1231] 54.8853640 47.8790092 130.2989282 73.0999611 79.8007978 76.0731884
## [1237] 76.8661813 76.6698649 61.4072270 177.2958397 178.5748502 178.7722313
## [1243] 140.5978745 94.9196406 97.0661472 93.2071361 89.6800771 162.0911657
## [1249] 28.1762785 28.5500182 30.2627266 88.2230516 91.8708442 91.7804334
## [1255] 85.1347691 87.5707645 61.3814483 18.0739275 15.3227344 16.3230292
## [1261] 171.6548032 150.7007446 147.1589902 151.9394264 131.0886215 126.1970409
## [1267] 120.5141666 153.2556949 146.3421179 158.4190874 142.5159763 144.1081946
## [1273] 151.8144902 155.8209810 155.3136718 90.3830428 80.1597124 121.5953628
## [1279] 117.5985812 174.8753739 218.4667098 162.4561452 180.7000289 171.9071503
## [1285] 202.9620580 162.9727504 147.8258609 174.8697130 153.4507630 159.1451246
## [1291] 169.5040674 160.9372374 2.0023564 95.8421046 83.4675229 99.0496345
## [1297] 55.1392423 64.3050211 46.2947234 137.6826462 82.2878853 88.5450076
## [1303] 84.2907670 85.3058753 85.1041895 69.0204629 186.2651613 187.6925811
## [1309] 188.1872649 146.5279299 102.0977079 103.8807059 100.8261336 97.0043793
## [1315] 170.1366415 23.1030477 23.4367995 24.2625915 96.3987131 99.9567205
## [1321] 99.8319832 93.6995394 96.1525418 68.8814451 27.5406604 23.7350146
## [1327] 25.2559321 181.0996757 160.0957556 156.6087188 161.3630869 139.7653448
## [1333] 135.3319703 130.0207889 160.3882756 153.4138181 165.0194715 149.0598798
## [1339] 150.5490237 158.8316338 162.7287963 162.1463284 99.9476479 89.6790587
## [1345] 127.3165717 121.9658646 181.9201813 226.0290685 171.6821648 189.7750670
## [1351] 180.8548297 211.7896592 171.4516045 156.0624166 182.9640141 161.5829594
## [1357] 167.4230941 177.4076779 168.6580715 93.8502103 81.4659721 97.0678240
## [1363] 53.6421227 62.7566244 44.9192514 135.7101674 81.4056053 87.9021639
## [1369] 83.8667804 84.7946627 84.5950979 67.0729406 184.5030905 185.9768303
## [1375] 186.6159088 144.5270370 102.0333840 103.9250127 100.6210984 96.8925549
## [1381] 168.2143929 22.3111050 22.6583984 23.7367622 95.9953431 99.5881559
## [1387] 99.4760189 93.1384830 95.5847780 68.6959396 26.0714268 21.9481281
## [1393] 23.5695650 179.5515710 158.5123201 155.0661981 159.7996739 137.9381230
## [1399] 133.6266303 128.5374787 158.4027909 151.4262310 163.0196673 147.0595360
## [1405] 148.5475770 156.8419289 160.7355712 160.1511153 98.5997423 88.2180546
## [1411] 125.3179897 120.0139851 181.9161264 225.8647946 170.7797439 188.9693610
## [1417] 180.1206008 211.1191123 170.9394572 155.6477590 182.6070692 161.2093305
## [1423] 166.9933380 177.1204856 168.4341464 13.9979864 5.1023224 59.8373841
## [1429] 54.6000137 76.1915977 42.6170616 86.4059252 99.0742464 105.4204140
## [1435] 102.6581536 102.6378713 28.8269659 104.2758196 108.7562880 118.8038740
## [1441] 53.2973871 129.6846300 134.9554456 123.5058095 124.4900657 77.7962196
## [1447] 90.6605523 90.8089024 93.9659516 112.9928296 116.5545804 116.9778485
## [1453] 105.1004328 106.1883161 105.8201938 75.1657433 73.9695267 73.8719132
## [1459] 113.9729924 93.3449897 93.2899948 95.8103365 57.1483623 64.0562315
## [1465] 77.1707200 64.6387790 57.6204596 69.4740925 53.6468420 55.3721474
## [1471] 63.0030173 66.8912414 66.3389863 69.4162789 59.0130555 36.2029807
## [1477] 43.6076089 196.2059121 228.4476032 144.1976450 164.6838052 160.7189647
## [1483] 191.0166083 163.8147394 155.7005590 181.0357250 162.1426629 164.3747573
## [1489] 179.5065866 174.9357528 18.7068055 53.7134786 50.4837288 62.2105954
## [1495] 56.3571723 84.9089699 97.5850186 102.7110357 100.3437636 100.2937821
## [1501] 21.1104072 117.7280389 121.9147831 130.8831754 63.4812218 127.2770046
## [1507] 132.2450305 121.5564840 121.8745184 91.7813776 77.0217675 77.1569560
## [1513] 80.2805934 111.4363159 115.1864471 115.5477515 103.8844504 105.2568447
## [1519] 100.8000120 64.7376568 62.5582811 62.8111058 125.6878008 104.6559640
## [1525] 104.0607142 106.9881110 70.1777884 75.3195240 85.5468608 77.8038651
## [1531] 70.7282060 81.5934224 65.6182107 67.0818455 75.9780034 79.6439813
## [1537] 78.9474888 72.7635002 61.0546025 44.7968826 46.0556493 197.4394425
## [1543] 231.8240507 150.6060888 171.1376083 166.3704109 197.2469635 167.6739985
## [1549] 158.2918014 184.3829644 164.7476059 167.5646622 182.2364077 176.9650471
## [1555] 60.5628607 54.6510571 80.8851529 38.7892532 85.1753966 97.7708414
## [1561] 104.5261012 101.6331159 101.6236346 30.9219304 99.2439731 103.6761356
## [1567] 113.7273128 52.1788360 128.5965760 133.9624940 122.2717790 123.4923635
## [1573] 73.3774813 94.7146933 94.8746181 98.0588430 111.6546904 115.1371968
## [1579] 115.5808666 103.6731886 104.6565950 105.7844537 77.4968797 76.7587803
## [1585] 76.4971784 108.9318806 88.3639204 88.3961280 90.8477083 52.0514114
## [1591] 59.1094133 72.8408664 61.3599552 54.4268777 67.0035740 51.3901610
## [1597] 53.2821772 59.9015836 63.9577822 63.5225977 66.6464504 56.7894280
## [1603] 36.2787491 46.0181174 193.7518001 225.2966575 140.2586960 160.7109273
## [1609] 156.9685894 187.0820079 160.5794107 152.8662764 177.9344685 159.2942986
## [1615] 161.3418203 176.5966106 172.2514304 9.4301866 69.8751927 94.8290651
## [1621] 37.6377724 49.0150588 51.4169830 49.8564591 49.7529534 32.6057124
## [1627] 133.0294225 133.7434087 133.1412251 112.7400156 75.7632106 80.2339426
## [1633] 70.9021834 70.1764534 122.2601710 65.1695348 65.5116137 68.4941201
## [1639] 61.8840400 65.8423294 66.0639450 55.4848357 57.4219214 47.1602212
## [1645] 27.6002696 32.8301410 30.5200413 125.9975225 105.1038918 101.4999857
## [1651] 106.3016348 88.4897933 81.4670579 74.8958374 118.4000197 112.0256923
## [1657] 126.2502127 111.2211892 113.3106794 117.6205815 122.0928273 122.0022130
## [1663] 45.5562780 34.6095822 96.0175782 99.7677628 151.2690065 190.3611916
## [1669] 122.3143242 141.7751077 134.2478515 165.8922962 129.4232736 116.6630816
## [1675] 143.9696658 122.8996653 127.2859416 140.1472824 133.1727528 75.5397766
## [1681] 87.1542119 35.6692458 48.0122892 52.3062167 50.1121764 50.0472394
## [1687] 29.8219627 123.6153131 124.3136850 123.8888854 106.6477419 76.8948283
## [1693] 81.7868690 71.3860936 71.4478375 113.5017534 73.1197310 73.4487385
## [1699] 76.5203584 61.6020786 65.4640701 65.7705577 54.4666043 56.1201475
## [1705] 51.2219534 36.8132525 41.5329180 39.3938812 116.7968581 95.8167100
## [1711] 92.3096673 97.0599067 79.3172065 72.0394409 65.9045395 110.6794598
## [1717] 104.4678927 119.0633584 104.3544198 106.5372195 110.0497016 114.5937539
## [1723] 114.5947548 37.5631084 25.9012031 90.7101729 96.2318304 149.7957411
## [1729] 187.4193613 116.0159161 135.8111983 128.7706845 160.4380478 125.3349781
## [1735] 113.4549697 140.5551001 119.7996015 123.7420728 137.2142447 130.7627559
## [1741] 117.8438869 106.7087003 116.7225569 116.0929003 115.7618559 115.6039544
## [1747] 60.0908312 179.0532857 182.5888691 188.8950550 117.3770124 138.0240584
## [1753] 141.0749269 134.9710886 132.4869815 153.8283940 25.5094097 25.3473260
## [1759] 26.9496540 127.9150625 131.8375613 131.9018890 122.9155874 125.1335250
## [1765] 104.6408539 52.6430633 44.7912636 47.5236876 182.8665263 161.3243115
## [1771] 159.4594251 163.2741908 131.0856137 132.8842767 136.1858899 137.6648424
## [1777] 130.5990012 138.8041405 123.1797248 124.0032729 135.4205543 138.4618738
## [1783] 137.4354844 112.3027653 99.7752640 98.0918131 86.8287441 217.2680570
## [1789] 258.6354200 191.5547927 211.3174233 204.0479224 235.7092196 199.0243788
## [1795] 185.6117130 212.9946915 191.6981609 196.4974612 208.6479112 201.0095341
## [1801] 110.5210077 122.1042696 130.7422578 127.2865911 127.3334272 68.9063488
## [1807] 70.5324618 77.1097996 93.4532734 31.0160048 153.0349283 158.7846902
## [1813] 146.0770865 148.5652304 36.5892193 133.2753513 133.4220872 136.5731285
## [1819] 135.2284708 138.1291947 138.6753762 127.0568597 127.3954014 135.9344776
## [1825] 115.1109944 115.0361443 114.5671376 90.9661066 74.4891634 77.2312603
## [1831] 77.3618252 34.1998335 51.0826027 74.3041350 23.5720453 17.3877404
## [1837] 32.8999839 21.4688638 24.1130037 22.9312700 27.5546078 27.7527923
## [1843] 84.1975700 79.1007768 32.4321347 53.2135142 207.6551091 232.7008326
## [1849] 141.5284072 160.8369079 159.8022552 186.9569404 168.5633169 164.6498942
## [1855] 186.7026801 170.7711464 171.1573458 187.0995896 184.7597162 12.7088796
## [1861] 20.2262996 16.8112411 16.8443692 65.0475965 127.9085335 126.1164458
## [1867] 118.9244924 134.9257020 43.4669240 48.9503131 37.1089928 38.5148126
## [1873] 129.0107504 98.1149655 98.4855442 101.0852973 26.6275625 30.3011460
## [1879] 30.6838295 18.9823868 20.4859064 30.1056640 57.6483121 65.0870537
## [1885] 62.2765611 111.1518991 93.0701441 87.8878090 93.2681215 92.1655944
## [1891] 78.5251403 61.1835098 132.9333951 127.6807668 143.4188531 130.2931626
## [1897] 132.7365668 133.0237252 137.7550771 138.1559059 30.7637245 31.4882411
## [1903] 121.2414292 129.6008368 114.1706540 152.7242915 89.3966672 107.6564334
## [1909] 99.1317333 130.4869813 92.3539943 79.0964572 106.4442738 85.2983321
## [1915] 89.8411455 102.5142965 95.5811507 10.6107852 6.7407266 6.9138876
## [1921] 77.5969169 134.8893596 132.3861187 123.1351523 147.1481040 31.1129166
## [1927] 36.7537554 24.5210733 26.4621081 138.8781262 106.1604258 106.5373812
## [1933] 108.9342666 13.9247661 17.6028085 17.9770319 6.4893977 8.4581912
## [1939] 26.6216847 65.9188730 73.6794984 70.8230614 115.2891277 98.6444206
## [1945] 93.0795217 98.4961877 101.9578327 87.1932866 67.5243705 144.1735584
## [1951] 139.1267746 154.9909610 142.1848358 144.6597317 144.3966812 149.1374228
## [1957] 149.6091829 39.8160385 43.0623122 133.7603590 142.3048445 102.2622073
## [1963] 141.9727494 84.7888599 101.7780650 92.4703122 123.2499879 83.3963605
## [1969] 69.0386145 96.4013046 75.0318583 80.1185204 91.9262178 84.4709496
## [1975] 3.9110922 3.7711699 82.1176845 145.4537245 142.9912417 133.6538401
## [1981] 154.8637094 24.5894798 29.5847320 19.5169163 19.1674677 148.7313332
## [1987] 103.3789625 103.7588224 105.9298517 12.1558699 15.9062226 15.8954823
## [1993] 11.2441050 13.5386493 17.8274746 63.9939092 71.9151798 69.0697634
## [1999] 125.8047645 109.2545822 103.6826268 109.0990664 111.8218621 97.4321987
## [2005] 78.1044865 153.1483507 147.9070624 163.6385551 150.4421030 152.8720913
## [2011] 153.2487418 157.9805538 158.3820897 49.7999756 51.7085108 140.7445080
## [2017] 148.1331345 101.2607711 143.0184597 92.3093453 108.2907288 98.4531727
## [2023] 128.5177555 87.2888596 71.7810112 98.8005382 77.3778861 83.1330067
## [2029] 93.5729365 85.3258352 0.2211656 79.9257224 141.5439127 139.0942961
## [2035] 129.8599699 151.6917293 27.0402443 32.3294375 21.2752457 21.8596309
## [2041] 144.9464096 103.8449774 104.2241508 106.4843891 12.2189800 16.1870078
## [2047] 16.3325749 8.6802948 11.1383852 20.5947820 64.0589112 71.9407309
## [2053] 69.0839118 122.0127953 105.3754609 99.8180135 105.2347501 108.0309226
## [2059] 93.5584480 74.1974962 149.5998455 144.4136424 160.1864900 147.1037460
## [2065] 149.5477865 149.7354656 154.4705870 154.8925507 45.9668146 48.2000734
## [2071] 137.7975626 145.5628007 101.9486128 142.9923128 89.7973523 106.1818321
## [2077] 96.5387341 126.8998392 86.1480533 71.0369243 98.2323877 76.7934504
## [2083] 82.3121353 93.2763230 85.3079937 79.8629901 141.6919935 139.2520079
## [2089] 130.0407211 151.7083900 27.0695355 32.3394278 21.3444778 21.8690266
## [2095] 145.0425486 103.6587180 104.0379203 106.2955113 12.3603728 16.3253617
## [2101] 16.4641349 8.8989748 11.3561028 20.3760777 63.8843254 71.7679712
## [2107] 68.9114056 122.1938373 105.5398663 99.9863561 105.4031376 108.1281305
## [2113] 93.6772235 74.3490841 149.6584815 144.4652264 160.2331753 147.1374353
## [2119] 149.5799814 149.7895707 154.5243079 154.9437325 46.0730305 48.2513426
## [2125] 137.7933937 145.5284468 102.0857564 143.1595217 90.0184423 106.4004190
## [2131] 96.7549058 127.1114942 86.3488822 71.2264129 98.4173422 76.9782736
## [2137] 82.5042721 93.4522101 85.4735973 120.9070110 123.6933242 128.8771837
## [2143] 82.0706810 106.7071309 111.5535203 101.1959117 101.2440035 101.2670348
## [2149] 67.9358754 68.1591046 71.4345313 91.3136149 95.1394621 95.4663378
## [2155] 83.9975408 85.5249761 79.6969728 46.5754177 46.1306179 45.7006502
## [2161] 122.7840057 101.2366939 99.4083986 103.1845020 73.0894506 72.9764808
## [2167] 76.9413183 91.9963146 85.1542065 97.9176194 82.2413083 84.0609943
## [2173] 90.6761859 94.8121671 94.4165396 57.5986931 45.0262310 64.3650843
## [2179] 67.1660322 178.6651039 214.7223388 137.4787879 157.8670502 152.0996887
## [2185] 183.4876248 151.3506648 140.8034958 167.4470002 147.2308540 150.5743090
## [2191] 164.7365912 158.8867500 8.8105924 32.3720569 95.2762665 160.4670610
## [2197] 166.1916249 153.3052083 157.9655335 40.6860829 188.7346975 188.9711466
## [2203] 192.2506487 143.8913685 145.1188293 145.7661156 136.9715257 136.0096995
## [2209] 157.9812699 159.5700205 162.5560045 161.0539496 35.4280455 38.3463290
## [2215] 44.5478427 39.7038283 48.0060826 51.6861439 67.3809728 67.5955149
## [2221] 70.5743666 79.7760970 82.8271201 84.6537017 70.6187689 72.6556241
## [2227] 74.4963481 97.4174989 101.9412058 102.7214189 123.6059201 187.8940665
## [2233] 199.2848313 107.6549528 121.8041420 125.6120042 144.5254781 142.2762910
## [2239] 145.8600711 159.6001289 150.5525867 147.8389205 163.0939794 164.7092393
## [2245] 23.7285831 102.9329788 156.9166665 162.5669473 149.8284769 154.6787807
## [2251] 49.0017414 191.2064144 191.4558593 194.7335782 140.7292778 141.7383453
## [2257] 142.3871819 134.0813448 132.9814223 156.2190200 160.6902443 164.0677692
## [2263] 162.4377882 27.4439853 34.1375385 40.1579675 34.9433028 51.7421620
## [2269] 52.3796861 65.0192916 75.6989424 78.3367105 88.1192392 90.5064401
## [2275] 92.4234857 78.6721187 80.8965397 82.7211129 96.0379556 101.5949001
## [2281] 109.4883877 130.3189758 181.2135558 191.4258159 100.3598701 113.9022317
## [2287] 118.0886591 136.2510054 135.3241649 139.6083554 152.4357474 144.1098337
## [2293] 141.1188064 156.1847917 158.1595852 121.7252210 144.4792180 149.8670012
## [2299] 137.6786954 142.9666333 70.4697111 194.5053847 194.7878223 198.0281093
## [2305] 129.5552013 129.9643397 130.6071015 123.7543315 122.3033292 148.5464316
## [2311] 160.6985048 165.0846485 163.1322673 7.8523069 28.1486367 31.8060898
## [2317] 26.8431658 62.7563180 56.0763515 59.0801935 96.1335970 97.7649552
## [2323] 109.1649689 109.5182818 111.6704561 98.9211094 101.6823476 103.4378149
## [2329] 90.9114639 99.0565061 125.6677613 146.0782755 160.7621796 168.5443042
## [2335] 78.9439070 91.0766092 96.0274824 112.7770480 114.4606920 120.3983862
## [2341] 131.0110861 124.3997372 120.7647983 135.3143341 138.1102035 178.2580049
## [2347] 183.8406024 171.5735392 173.4313579 55.5936199 137.2924620 137.3562384
## [2353] 140.2243465 160.7584207 163.9561070 164.4588048 152.6074997 153.2475875
## [2359] 157.5359985 127.9775615 126.0393816 126.2556254 120.0797975 104.8880324
## [2365] 107.9493699 107.7715829 65.0990700 82.0739841 104.8987306 29.0954868
## [2371] 24.7481698 23.0163284 12.4506089 10.8572000 25.9269905 26.1369096
## [2377] 24.4294995 111.4161210 104.3573403 19.4654329 34.8499904 237.0405567
## [2383] 263.3311417 172.4925799 191.8489117 190.7168159 217.9724782 198.9757614
## [2389] 194.3642274 217.0531695 200.5770346 201.2841266 217.1567410 214.3978639
## [2395] 5.8812757 7.2663202 5.6361669 168.2467456 122.9755673 123.3536183
## [2401] 125.1816937 17.8846853 15.5932239 14.9666191 26.0088205 25.9425194
## [2407] 33.6648467 85.3958523 93.2918266 90.5211134 136.6982734 122.7791748
## [2413] 116.8009999 122.1125703 131.4510446 115.6348210 93.7244299 174.8553009
## [2419] 169.9596665 185.8915007 173.2460730 175.7308736 175.1750738 179.9178357
## [2425] 180.4377542 69.6871050 74.1185533 164.7032964 172.5941472 79.9600483
## [2431] 124.1165198 89.6947963 102.0241404 91.1060500 118.3864148 75.3122690
## [2437] 58.2027696 83.1803589 62.5953775 69.4340699 76.6877612 67.3036617
## [2443] 13.1397180 10.4704387 174.1278341 125.2170347 125.5930309 127.3007370
## [2449] 23.7297599 21.4649650 20.8413250 31.8195961 31.8098061 36.4340762
## [2455] 88.4444994 96.2849127 93.5564928 142.1043296 128.4323576 122.4319938
## [2461] 127.7280545 137.3300241 121.5100640 99.5349404 180.6626482 175.7373617
## [2467] 191.6523668 178.9355582 181.4125723 180.9649985 185.7076539 186.2171090
## [2473] 75.5411336 79.8071457 170.1205960 177.7175888 78.0880028 123.0867994
## [2479] 93.3511896 104.8374706 93.7595301 120.1694396 76.9522850 59.6441835
## [2485] 83.6072180 63.5709304 70.6458888 76.7388318 67.0364111 5.9621198
## [2491] 161.0033636 121.0319085 121.4115554 123.3916546 10.8538356 8.3269569
## [2497] 7.7016509 19.0321422 18.7833177 31.9476280 82.5214490 90.4538777
## [2503] 87.6385109 129.8795480 115.6927149 109.7391273 115.0660843 124.2217667
## [2509] 108.3705859 86.4902938 167.7902135 162.9498153 178.9100913 166.3884236
## [2515] 168.8858131 168.1424462 172.8849992 173.4239005 62.5374747 67.3017272
## [2521] 158.2811364 166.6103493 82.3287165 125.2640222 85.1072571 98.4646064
## [2527] 87.7940425 116.0674014 73.3875144 56.7093193 82.7201010 61.6367197
## [2533] 68.1033655 76.7416831 67.8357387 164.5878304 117.6814058 118.0600293
## [2539] 119.9325044 14.1993585 13.0126363 12.3668922 21.9486425 22.3056835
## [2545] 28.3226319 79.8745083 87.7802002 85.0005340 135.1505634 120.5633045
## [2551] 114.6644041 120.0176964 127.7194779 112.2456829 90.8999012 170.5765960
## [2557] 165.5732744 181.4497764 168.6219082 171.0893635 170.8299883 175.5716538
## [2563] 176.0553514 65.7138220 69.5161378 159.6542087 167.2873533 85.2724403
## [2569] 129.0599201 91.0590336 104.2766547 93.5464914 121.5443539 78.6957527
## [2575] 61.8218327 87.3937882 66.5226252 73.1647002 81.1425499 71.9590976
## [2581] 167.9047076 168.0785460 171.2901818 150.5054789 152.7017584 153.3136592
## [2587] 142.6473673 142.3756847 157.4564826 145.6889508 146.7830536 145.9165996
## [2593] 70.8295021 61.9739509 67.0609451 64.6177318 36.9210936 53.1591931
## [2599] 77.4502991 27.0769294 30.9571303 39.1189078 43.2384308 44.7720216
## [2605] 30.1759361 31.9757058 33.8224218 99.0631057 98.4299121 66.0182661
## [2611] 86.6471107 210.6142954 228.7256705 135.6153155 152.6611414 154.2386681
## [2617] 177.3541974 167.4052494 167.2741324 185.4882089 172.8105129 171.6060779
## [2623] 187.5172396 187.1801064 0.3800265 3.5315777 115.5240497 119.2678618
## [2629] 119.2174981 111.8368318 114.2240529 89.3590078 40.4719496 33.1554832
## [2635] 35.9055249 187.8650816 166.4110401 163.6578901 168.0164156 141.0140409
## [2641] 139.5665204 138.2966238 154.7359938 147.6451871 157.5432155 141.6201747
## [2647] 142.7668465 152.8014910 156.2793327 155.4548776 110.5810367 98.9692430
## [2653] 117.8270463 109.1330753 202.9332036 246.2039195 186.5941919 205.5024291
## [2659] 197.2259069 228.5990836 189.5565362 174.8673099 202.0737051 180.6345249
## [2665] 186.0994282 196.9515243 188.5796086 3.2796562 115.9038528 119.6477883
## [2671] 119.5974662 112.2150194 114.6020227 89.7376690 40.8435878 33.5192420
## [2677] 36.2716646 188.1530272 166.6959595 163.9511235 168.3049045 141.2409266
## [2683] 139.8310578 138.6055192 154.8585471 147.7670809 157.6345898 141.7150418
## [2689] 142.8555294 152.9181481 156.3884107 155.5600172 110.9156462 99.2944728
## [2695] 117.8908310 109.1334780 203.3114014 246.5838914 186.9551640 205.8679492
## [2701] 197.5951990 228.9701217 189.9334170 175.2461886 202.4530194 181.0138347
## [2707] 186.4779434 197.3314042 188.9596329 118.0832734 121.7987545 121.7351418
## [2713] 114.5460698 116.9454935 91.6228376 43.4443466 36.2790188 38.9894017
## [2719] 191.3815542 169.9312301 167.1666711 171.5322301 144.5178580 143.0980800
## [2725] 141.7710300 157.9405064 150.8472556 160.6105207 144.7045941 145.8222290
## [2731] 155.9816319 159.4268925 158.5851585 113.9490056 102.3858110 120.7608117
## [2737] 111.7040886 205.1380814 248.6214662 189.7228153 208.5613198 200.2145986
## [2743] 231.5478398 192.3237588 177.5209742 204.6866226 183.2495499 188.7785680
## [2749] 199.4843479 191.0355482 3.9744973 4.1863435 8.1784328 8.1339333
## [2755] 28.8340349 76.0205955 83.9282237 81.0766633 121.7175180 106.6474128
## [2761] 100.8024218 106.1770231 113.6684510 98.0704524 76.7446773 156.9817393
## [2767] 152.1149087 168.0668470 155.5358544 158.0342905 157.3167580 162.0594701
## [2773] 162.5905923 51.8116281 56.4595562 147.5914542 156.2279119 89.7320457
## [2779] 130.9659462 82.3267944 97.4279262 87.2999220 116.9411060 75.3417750
## [2785] 59.6641375 86.6474934 65.2284303 71.0338576 81.4334496 73.2680087
## [2791] 0.6488994 11.4640590 10.7420876 31.9157316 79.8736624 87.7883967
## [2797] 84.9394045 122.1455750 107.6121838 101.6934554 107.0391227 115.9382246
## [2803] 100.0453448 78.2124059 159.7052441 154.9335932 170.9260386 158.5592152
## [2809] 161.0714385 160.0973043 164.8388853 165.4009826 54.3729609 59.6027916
## [2815] 150.9939486 159.8576995 85.7616664 127.1203859 80.3744342 94.9470501
## [2821] 84.6497776 113.9654475 72.0682903 56.1607170 83.0191343 61.6264244
## [2827] 67.5579110 77.6871865 69.4248080 11.9149118 11.2803058 31.6766306
## [2833] 79.8858271 87.8046503 84.9575876 122.7888391 108.2610682 102.3423149
## [2839] 107.6878991 116.5444616 100.6689541 78.8544926 160.2726031 155.4901514
## [2845] 171.4779850 159.0892060 161.5994781 160.6583604 165.4001440 165.9586832
## [2851] 54.9516305 60.1101375 151.4567905 160.2618695 85.6288965 127.1239874
## [2857] 80.8511312 95.3445427 85.0188906 114.2664679 72.3007370 56.3259834
## [2863] 83.1337826 61.7544877 67.7301425 77.7499024 69.4334306 2.4719552
## [2869] 29.0001632 71.7675068 79.5851488 76.7257204 115.9028032 100.1066776
## [2875] 94.3728769 99.7747629 105.7726835 90.4167391 69.6494561 148.8480721
## [2881] 143.9567412 159.9004586 147.3577292 149.8567011 149.1671914 153.9099558
## [2887] 154.4337858 43.7835779 48.2900736 139.5422668 148.4303974 95.7854602
## [2893] 135.7265003 81.1929150 97.5015426 87.8762898 118.3141080 77.8448385
## [2899] 63.0972633 90.4108333 68.9993636 74.2746493 85.7601175 78.1584182
## [2905] 31.3475878 74.1111743 81.9141155 79.0551792 114.4547715 98.9494004
## [2911] 93.1635063 98.5550609 105.5454954 89.9439593 68.7728910 149.0226118
## [2917] 144.2183917 160.2010830 147.8173974 150.3301830 149.3938706 154.1359879
## [2923] 154.6884742 43.7563572 48.8902478 140.4160830 149.5977528 93.8963470
## [2929] 133.5342782 78.8061213 95.0475031 85.4078861 115.8435243 75.4195835
## [2935] 60.7581942 88.0918408 66.6939708 71.9084261 83.5180359 76.0152055
## [2941] 52.0139609 59.8510210 57.1236819 140.7334095 123.0731995 117.7958015
## [2947] 123.1935653 120.9015202 108.1770199 91.2596664 159.0445511 153.3082471
## [2953] 168.5571566 154.4615039 156.7578505 158.8015649 163.4718238 163.6778094
## [2959] 60.6543608 59.0274403 141.9217060 146.8455258 113.5882382 157.1688704
## [2965] 110.1367706 125.9959028 116.0301643 145.7733184 103.9772879 87.8913883
## [2971] 114.4123873 93.1495973 99.3102281 108.6266786 99.7833000 7.9344140
## [2977] 5.1260784 153.5829884 132.6298405 129.0880717 133.8654989 113.7816218
## [2983] 108.3132262 102.4816876 138.4051359 131.6270743 144.4825487 128.7621791
## [2989] 130.5315399 137.1713848 141.3528262 140.9799076 72.6080383 62.1492822
## [2995] 109.5290731 108.1650147 164.8490108 206.9863780 146.4166787 165.1400580
## [3001] 156.7725095 188.1282144 149.2598980 134.8641602 162.1704545 140.7469432
## [3007] 146.0124684 157.3340592 149.2883867 2.8596097 158.1119611 136.9492058
## [3013] 133.6635319 138.3106423 116.0434999 111.7377466 107.4313676 138.0573743
## [3019] 131.1674827 143.4410872 127.5798129 129.2265353 136.6573055 140.7045624
## [3025] 140.2290792 78.3583014 67.3383364 107.2256233 104.4409346 172.7806329
## [3031] 214.8933833 153.4493902 172.3532526 164.1347623 195.5590722 156.9552623
## [3037] 142.6722986 169.9959051 148.5799497 153.7945579 165.2078394 157.1957929
## [3043] 156.1136598 135.0116880 131.6453939 136.3341704 114.7664578 110.0760382
## [3049] 105.2906794 137.6964668 130.8440250 143.3331720 127.5172549 129.2096727
## [3055] 136.3556766 140.4528778 140.0143429 75.9706596 65.1037696 107.5695974
## [3061] 105.3304701 169.9669025 212.0409484 150.7351650 169.5974181 161.3459162
## [3067] 192.7567417 154.1068923 139.8133734 167.1364420 145.7203606 150.9371857
## [3073] 162.3496522 154.3436354 21.5624321 24.4993730 19.8522311 58.9645094
## [3079] 50.4545136 51.6043037 95.5537745 96.6217511 108.8566056 108.0647933
## [3085] 110.3197155 98.2100872 101.2646088 102.9642757 83.3479673 91.7594391
## [3091] 122.8449912 142.9832588 154.5876256 163.9887952 73.1837091 86.4697408
## [3097] 90.7231405 109.1361488 108.4414349 113.7168484 125.3080237 117.8971362
## [3103] 114.5154888 129.3169515 131.7513446 6.2094104 2.8842012 40.7250369
## [3109] 29.3531269 32.0357332 83.2842046 82.9860694 96.9185301 93.4806267
## [3115] 95.9242454 85.5536911 89.2375066 90.7606418 63.8689518 71.2455554
## [3121] 105.2588944 124.7601576 151.3335774 166.8660043 73.7910085 90.7290676
## [3127] 92.3708527 115.7293447 106.6664992 108.6326208 124.5119538 113.6502888
## [3133] 111.5606811 127.2095368 127.9578180 5.4168553 43.0916359 29.4085993
## [3139] 27.3210295 87.4084603 86.7101282 101.0511323 96.8216045 99.3164620
## [3145] 89.5540444 93.3892700 94.8552358 59.2137088 67.2817788 107.2842112
## [3151] 126.3745385 145.3909339 161.6652650 68.5554320 86.0166660 87.1836070
## [3157] 111.3574209 100.9450864 102.5920486 118.8668809 107.6675041 105.6998406
## [3163] 121.4082306 121.9936217 43.5607215 31.7624576 32.5396208 86.1196033
## [3169] 85.8557672 99.7506946 96.3636633 98.8062569 88.4017688 92.0685995
## [3175] 93.5981076 64.4446499 72.2395101 108.0831368 127.5403283 149.2787273
## [3181] 164.3288942 71.2945820 88.0491473 89.8447872 112.9676149 104.4241733
## [3187] 106.7122837 122.2109465 111.6509585 109.4321633 125.0240411 125.9322955
## [3193] 18.3196278 43.1317612 47.8400807 45.5223984 61.0726696 54.4502757
## [3199] 57.0260021 49.3430593 53.7246335 54.8837889 62.1439277 61.9379983
## [3205] 64.5434365 84.2401203 177.8149264 200.1439109 108.0845584 127.0456968
## [3211] 126.5389550 153.0281683 136.7243961 134.4359179 154.9342624 140.3105987
## [3217] 139.9816455 155.9924732 154.5554596 24.8967250 66.1586689 63.6824245
## [3223] 79.3536738 72.0399027 74.6551438 67.6298847 72.0359793 73.1770332
## [3229] 47.7945192 50.5612468 79.0761277 97.5302681 159.5361068 182.0689987
## [3235] 90.4528975 109.7949914 108.7735004 135.9862207 118.4648054 116.1447558
## [3241] 136.6715944 122.0019666 121.6666576 137.6771443 136.2572642 90.8889600
## [3247] 88.0723157 103.9313988 95.6637142 98.3044936 92.2394532 96.7174510
## [3253] 97.7957106 31.9054324 40.3698718 99.3298794 115.9734462 134.6858642
## [3259] 158.4405651 68.5824706 88.7079671 86.3031631 115.1400877 94.2820146
## [3265] 91.3183562 112.4456304 97.2302880 97.1244121 113.1198017 111.4463922
## [3271] 7.0965557 13.6438464 17.2966292 18.2758363 3.1742796 5.9920983
## [3277] 7.4856612 105.3840979 101.4456015 42.7649150 62.2798516 225.5468542
## [3283] 247.5869605 154.9841895 173.2679588 173.5725148 198.7642247 184.4945145
## [3289] 182.2029631 202.7051258 188.1148214 187.8204520 203.8314332 202.3342098
## [3295] 16.1446052 12.3159562 14.0884381 5.5960864 10.1671998 10.4824415
## [3301] 100.7589458 96.2138839 36.3852571 56.3944663 222.4651251 245.6663066
## [3307] 153.4639502 172.1300543 171.9749014 197.8729141 182.1347473 179.2224131
## [3313] 200.3375087 185.2219292 185.1893770 201.1890800 199.3629739 15.9841902
## [3319] 14.8181335 11.7316273 7.6838083 6.2281314 116.8236054 111.9997914
## [3325] 40.9954700 57.8642865 238.4595619 261.0594668 168.5475170 186.8917332
## [3331] 187.1221760 212.4058350 197.7970287 195.1761128 216.0069319 201.1427007
## [3337] 200.9944593 217.0018850 215.3158977 2.6452145 14.2282984 15.7630441
## [3343] 14.4511728 105.0388630 99.1300257 26.1466300 45.0474496 229.1100406
## [3349] 253.9691728 162.4299926 181.4944778 180.8037099 207.4647863 189.9443972
## [3355] 186.1184533 208.0987798 192.2395963 192.6021235 208.5514956 206.2271829
## [3361] 15.1192765 15.8694984 14.3436084 107.6059234 101.6123872 26.4177549
## [3367] 44.5772088 231.7498157 256.6011289 165.0309924 184.0716239 183.4130237
## [3373] 210.0259043 192.5856676 188.7620502 210.7410125 194.8840368 195.2470658
## [3379] 211.1966378 208.8702017 4.7427646 5.5567233 105.8494995 101.5430904
## [3385] 39.9341244 59.2624744 226.8150143 249.3409098 156.8744073 175.2975704
## [3391] 175.4383042 200.8816398 186.0669489 183.5109346 204.2770236 189.4623708
## [3397] 189.2807330 205.2891852 203.6491561 1.8760094 110.5863631 106.2763864
## [3403] 41.9092822 60.4428039 231.3413029 253.5577495 160.9725909 179.2587526
## [3409] 179.5588730 204.7462521 190.4173271 188.0165201 208.6281670 193.9477094
## [3415] 193.7025615 209.7129238 208.1517770 111.2007763 106.6925220 40.5680592
## [3421] 58.8685339 232.3701302 254.8374143 162.3195263 180.6746510 180.8940632
## [3427] 206.2056044 191.6046787 189.0674320 209.8150911 195.0190447 194.8322929
## [3433] 210.8410771 209.2057261 12.7336985 100.4882652 112.6645654 127.2412571
## [3439] 159.2713246 80.1144493 100.3923342 94.5067973 125.8972170 94.9278146
## [3445] 86.2846351 111.8186561 92.7263921 95.0750638 110.1007793 105.6049965
## [3451] 91.8975658 102.5904775 137.2151374 170.7754434 92.8453911 113.1067828
## [3457] 107.0993915 138.5474332 106.7845982 97.2854384 123.3423416 103.7423137
## [3463] 106.5146574 121.2150240 116.1810245 20.8928832 227.5450643 256.5620454
## [3469] 167.8867876 187.8577354 185.5964580 214.2461580 191.8009652 185.6646452
## [3475] 209.6134719 192.0108216 193.3814062 209.0130335 205.4426635 239.7209433
## [3481] 271.0615463 184.4102037 204.6587141 201.6628835 231.0938375 206.2813211
## [3487] 198.8644910 223.7684698 205.2873733 207.2387036 222.5625049 218.2695476
## [3493] 46.9277282 82.1166193 76.3117289 67.2861890 72.5431351 46.4186691
## [3499] 43.4148737 32.2811945 37.8209870 40.0970298 25.8820862 23.4460898
## [3505] 93.1104206 77.5262637 74.4972760 58.3570599 64.8063043 73.9961482
## [3511] 47.4545851 67.6232473 64.2609097 50.2290161 57.6979915 20.5328970
## [3517] 18.6432823 46.8239466 35.6979538 44.8966475 52.1256065 47.3992788
## [3523] 42.5866948 56.4560726 60.1293506 11.4039178 26.4351236 33.3527913
## [3529] 48.6384035 44.0961463 48.4032719 41.5471260 50.8169021 57.6510584
## [3535] 31.6698159 22.5244635 37.2564192 35.6569904 37.2595416 30.6425326
## [3541] 41.4442324 47.3349586 43.2323561 60.6006955 42.8632086 57.5446975
## [3547] 50.1098182 51.2554528 60.8988035 17.3829543 18.2108414 15.3319192
## [3553] 8.1977724 20.8757132 25.0175150 27.3834325 6.4568780 11.4214231
## [3559] 23.9555295 20.1406660 21.4392145 16.8729240 8.4172975 18.4838567
## [3565] 7.4749251 17.5101441 14.3751247 16.0110985 17.5430182 10.3114926
aquifer_pair$from
## [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [25] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [49] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [73] 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2
## [97] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [121] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [145] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3
## [169] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
## [193] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
## [217] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
## [241] 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
## [265] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
## [289] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
## [313] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5
## [337] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
## [361] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
## [385] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
## [409] 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
## [433] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
## [457] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
## [481] 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
## [505] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
## [529] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
## [553] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8
## [577] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
## [601] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
## [625] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9
## [649] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
## [673] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
## [697] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
## [721] 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
## [745] 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
## [769] 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
## [793] 10 10 10 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11
## [817] 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11
## [841] 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11
## [865] 11 11 11 11 11 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12
## [889] 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12
## [913] 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12
## [937] 12 12 12 12 12 12 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13
## [961] 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13
## [985] 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13
## [1009] 13 13 13 13 13 13 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14
## [1033] 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14
## [1057] 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14
## [1081] 14 14 14 14 14 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15
## [1105] 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15
## [1129] 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15
## [1153] 15 15 15 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16
## [1177] 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16
## [1201] 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16
## [1225] 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17
## [1249] 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17
## [1273] 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 18 18 18 18
## [1297] 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18
## [1321] 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18
## [1345] 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 19 19 19 19 19 19 19 19 19
## [1369] 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19
## [1393] 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19
## [1417] 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
## [1441] 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
## [1465] 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
## [1489] 20 20 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21
## [1513] 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21
## [1537] 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 22 22 22 22 22 22
## [1561] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22
## [1585] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22
## [1609] 22 22 22 22 22 22 22 22 22 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23
## [1633] 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23
## [1657] 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 24
## [1681] 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24
## [1705] 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24
## [1729] 24 24 24 24 24 24 24 24 24 24 24 24 25 25 25 25 25 25 25 25 25 25 25 25
## [1753] 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25
## [1777] 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25
## [1801] 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26
## [1825] 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26
## [1849] 26 26 26 26 26 26 26 26 26 26 26 27 27 27 27 27 27 27 27 27 27 27 27 27
## [1873] 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27
## [1897] 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 28 28 28
## [1921] 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28
## [1945] 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28
## [1969] 28 28 28 28 28 28 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29
## [1993] 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29
## [2017] 29 29 29 29 29 29 29 29 29 29 29 29 29 29 30 30 30 30 30 30 30 30 30 30
## [2041] 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30
## [2065] 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 31 31 31
## [2089] 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31
## [2113] 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31 31
## [2137] 31 31 31 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32
## [2161] 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32 32
## [2185] 32 32 32 32 32 32 32 32 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
## [2209] 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
## [2233] 33 33 33 33 33 33 33 33 33 33 33 33 34 34 34 34 34 34 34 34 34 34 34 34
## [2257] 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34
## [2281] 34 34 34 34 34 34 34 34 34 34 34 34 34 34 34 35 35 35 35 35 35 35 35 35
## [2305] 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35
## [2329] 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 36 36 36 36 36 36 36
## [2353] 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36
## [2377] 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 37 37 37 37 37 37
## [2401] 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37
## [2425] 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 38 38 38 38 38 38
## [2449] 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38
## [2473] 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 38 39 39 39 39 39 39 39
## [2497] 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39
## [2521] 39 39 39 39 39 39 39 39 39 39 39 39 39 39 39 40 40 40 40 40 40 40 40 40
## [2545] 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40
## [2569] 40 40 40 40 40 40 40 40 40 40 40 40 41 41 41 41 41 41 41 41 41 41 41 41
## [2593] 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41 41
## [2617] 41 41 41 41 41 41 41 41 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42
## [2641] 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42
## [2665] 42 42 42 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43
## [2689] 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 43 44 44 44
## [2713] 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44 44
## [2737] 44 44 44 44 44 44 44 44 44 44 44 44 44 44 45 45 45 45 45 45 45 45 45 45
## [2761] 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45
## [2785] 45 45 45 45 45 45 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46
## [2809] 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 47 47 47
## [2833] 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47
## [2857] 47 47 47 47 47 47 47 47 47 47 47 48 48 48 48 48 48 48 48 48 48 48 48 48
## [2881] 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48
## [2905] 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49 49
## [2929] 49 49 49 49 49 49 49 49 49 49 49 49 50 50 50 50 50 50 50 50 50 50 50 50
## [2953] 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 51
## [2977] 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51
## [3001] 51 51 51 51 51 51 51 51 51 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52
## [3025] 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 53 53 53 53 53 53
## [3049] 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53
## [3073] 53 53 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54
## [3097] 54 54 54 54 54 54 54 54 54 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55
## [3121] 55 55 55 55 55 55 55 55 55 55 55 55 55 55 55 56 56 56 56 56 56 56 56 56
## [3145] 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 57 57 57 57
## [3169] 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57
## [3193] 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58
## [3217] 58 58 58 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59
## [3241] 59 59 59 59 59 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60
## [3265] 60 60 60 60 60 60 61 61 61 61 61 61 61 61 61 61 61 61 61 61 61 61 61 61
## [3289] 61 61 61 61 61 61 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62
## [3313] 62 62 62 62 62 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63
## [3337] 63 63 63 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64
## [3361] 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 66 66 66 66
## [3385] 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 67 67 67 67 67 67 67 67 67
## [3409] 67 67 67 67 67 67 67 67 67 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68
## [3433] 68 68 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 70 70 70 70 70 70
## [3457] 70 70 70 70 70 70 70 70 70 71 71 71 71 71 71 71 71 71 71 71 71 71 71 72
## [3481] 72 72 72 72 72 72 72 72 72 72 72 72 73 73 73 73 73 73 73 73 73 73 73 73
## [3505] 74 74 74 74 74 74 74 74 74 74 74 75 75 75 75 75 75 75 75 75 75 76 76 76
## [3529] 76 76 76 76 76 76 77 77 77 77 77 77 77 77 78 78 78 78 78 78 78 79 79 79
## [3553] 79 79 79 80 80 80 80 80 81 81 81 81 82 82 82 83 83 84
aquifer_pair$lags
## [1] 3 3 3 4 3 4 4 4 4 4 4 4 4 3 4 5 5 5 2 2 2 3 3 4
## [25] 1 4 4 4 4 4 2 3 3 4 2 5 6 5 5 2 5 5 5 5 5 5 4 4
## [49] 5 4 4 4 4 3 3 3 1 2 3 2 2 3 2 2 2 2 2 3 3 2 3 7
## [73] 8 5 6 6 7 6 6 7 6 6 7 7 1 1 5 6 5 5 5 5 5 5 5 4
## [97] 1 4 5 5 5 4 4 4 3 3 6 4 2 3 3 3 3 4 4 4 3 5 3 4
## [121] 3 3 4 6 6 6 3 3 3 3 2 4 4 5 5 3 2 2 2 3 2 1 5 5
## [145] 5 5 5 5 5 5 2 2 5 6 5 5 2 3 3 4 3 3 4 3 3 4 4 1
## [169] 4 5 4 4 4 4 4 4 4 4 2 4 4 5 4 3 3 3 3 2 5 4 2 2
## [193] 3 2 2 3 4 4 4 5 3 3 3 3 4 5 5 5 3 3 3 2 2 3 4 4
## [217] 4 3 3 2 3 3 2 1 4 4 5 4 4 4 5 5 1 1 4 5 5 6 3 4
## [241] 4 5 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 2 4 4 5 5
## [265] 4 4 4 3 3 5 4 2 2 2 2 2 4 4 4 4 5 3 3 3 3 5 5 5
## [289] 5 2 2 2 2 2 3 4 4 4 3 3 3 3 3 3 2 5 5 5 5 5 5 5
## [313] 5 1 2 5 6 4 6 3 3 3 4 3 3 4 3 3 4 4 1 1 1 2 1 2
## [337] 1 1 7 5 3 2 3 2 2 2 3 2 3 1 4 4 4 4 4 4 2 6 6 7
## [361] 4 5 5 5 5 5 2 2 2 5 5 5 5 5 4 2 2 2 6 6 6 6 4 5
## [385] 5 5 4 5 4 4 5 5 5 4 3 3 3 8 10 7 8 7 9 7 7 8 7 7
## [409] 8 7 2 2 2 2 2 2 1 7 6 3 3 3 3 2 2 2 3 3 2 4 4 5
## [433] 5 5 5 2 6 6 7 3 6 6 6 6 5 3 3 3 5 6 6 5 5 5 3 3
## [457] 3 6 6 6 6 4 5 5 4 4 4 4 4 4 4 4 4 4 3 2 9 10 7 8
## [481] 8 9 8 7 8 8 8 8 8 1 1 1 1 1 1 7 5 2 2 2 2 3 2 3
## [505] 2 2 1 4 4 4 4 4 4 2 6 6 7 4 5 5 5 5 5 2 2 2 4 5
## [529] 5 4 4 4 2 2 2 6 5 5 6 4 4 5 5 5 5 4 4 5 5 5 4 3
## [553] 4 3 8 9 7 7 7 8 7 6 7 7 7 7 7 1 1 1 1 1 7 6 2 1
## [577] 2 1 3 3 3 2 3 1 5 4 4 4 4 4 2 7 7 7 5 5 5 5 5 6
## [601] 1 1 1 4 5 5 4 4 3 2 1 1 7 6 6 6 5 5 5 6 5 6 5 5
## [625] 5 6 6 4 3 4 4 8 9 7 8 7 8 7 7 8 7 7 7 7 1 1 1 1
## [649] 8 6 2 1 1 1 3 3 4 2 3 1 5 4 4 4 4 4 3 7 7 7 5 5
## [673] 5 5 5 6 1 1 1 4 5 5 4 4 4 2 1 1 7 6 6 6 5 5 5 6
## [697] 6 6 5 5 6 6 6 4 4 4 4 8 9 7 8 7 9 7 7 8 7 7 7 7
## [721] 1 1 1 7 6 2 2 2 2 3 2 3 3 3 1 4 4 4 4 4 4 2 6 7
## [745] 7 4 5 5 5 5 6 2 2 2 5 5 5 5 5 4 2 2 2 7 6 6 6 5
## [769] 5 5 5 5 5 5 5 5 5 5 4 4 4 3 8 10 7 8 7 9 7 7 8 7
## [793] 7 8 7 1 1 7 6 2 1 1 1 3 3 3 2 3 1 5 4 4 4 4 4 2
## [817] 7 7 7 5 5 5 5 5 6 1 1 1 4 5 5 4 4 3 2 1 1 7 6 6
## [841] 6 5 5 5 6 5 6 5 5 6 6 6 4 4 4 4 8 9 7 8 7 8 7 7
## [865] 8 7 7 7 7 1 7 6 2 2 2 2 3 3 3 2 3 1 5 4 4 4 4 4
## [889] 2 7 7 7 5 5 5 5 5 6 1 1 1 4 5 5 4 4 4 2 1 1 7 6
## [913] 6 6 5 5 5 5 5 6 5 5 5 6 5 4 4 4 4 8 9 7 8 7 8 7
## [937] 7 8 7 7 7 7 7 6 2 2 2 2 3 2 3 3 3 1 4 4 4 4 4 4
## [961] 2 6 7 7 4 5 5 5 5 5 2 2 2 5 5 5 5 5 4 2 2 2 7 6
## [985] 6 6 5 5 5 5 5 5 4 4 5 5 5 4 4 4 3 8 10 7 8 7 9 7
## [1009] 7 8 7 7 8 7 3 7 8 8 8 5 5 5 6 6 8 4 6 6 6 6 6 6
## [1033] 1 1 2 5 7 7 7 7 3 8 8 8 6 6 6 6 6 7 7 7 7 2 2 2
## [1057] 2 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 8 8 5 5 5 6 6 6
## [1081] 6 6 6 7 7 5 6 6 6 4 4 4 4 4 6 4 3 3 4 4 4 4 3 3
## [1105] 2 5 4 4 4 4 4 6 6 6 4 4 4 3 3 4 5 5 5 2 1 1 1 2
## [1129] 2 1 4 4 5 4 5 4 4 4 2 3 5 5 5 6 3 3 3 4 4 4 4 4
## [1153] 4 4 4 1 2 1 4 3 4 2 2 3 5 3 3 3 3 3 2 7 7 6 5 3
## [1177] 4 3 3 6 2 2 2 3 3 3 3 3 2 1 1 1 6 5 5 5 5 5 4 6
## [1201] 6 6 5 6 6 6 6 3 3 5 5 6 8 6 6 6 7 6 5 6 6 6 6 6
## [1225] 1 1 4 3 4 2 3 2 5 3 3 3 3 3 3 7 7 7 6 4 4 4 4 6
## [1249] 2 2 2 4 4 4 4 4 3 1 1 1 7 6 6 6 5 5 5 6 6 6 6 6
## [1273] 6 6 6 4 3 5 5 7 9 6 7 7 8 7 6 7 6 6 7 6 1 4 4 4
## [1297] 3 3 2 6 4 4 4 4 4 3 7 7 7 6 4 4 4 4 7 1 1 1 4 4
## [1321] 4 4 4 3 2 1 1 7 6 6 6 6 5 5 6 6 7 6 6 6 7 6 4 4
## [1345] 5 5 7 9 7 8 7 8 7 6 7 6 7 7 7 4 4 4 2 3 2 6 4 4
## [1369] 4 4 4 3 7 7 7 6 4 4 4 4 7 1 1 1 4 4 4 4 4 3 1 1
## [1393] 1 7 6 6 6 6 5 5 6 6 7 6 6 6 6 6 4 4 5 5 7 9 7 7
## [1417] 7 8 7 6 7 6 7 7 7 1 1 3 3 3 2 4 4 4 4 4 2 4 5 5
## [1441] 2 5 5 5 5 3 4 4 4 5 5 5 4 4 4 3 3 3 5 4 4 4 3 3
## [1465] 3 3 3 3 2 3 3 3 3 3 3 2 2 8 9 6 7 6 8 7 6 7 6 7
## [1489] 7 7 1 2 2 3 3 4 4 4 4 4 1 5 5 5 3 5 5 5 5 4 3 3
## [1513] 3 5 5 5 4 4 4 3 3 3 5 4 4 4 3 3 4 3 3 4 3 3 3 3
## [1537] 3 3 3 2 2 8 9 6 7 7 8 7 6 7 7 7 7 7 3 3 3 2 4 4
## [1561] 4 4 4 2 4 4 5 2 5 5 5 5 3 4 4 4 5 5 5 4 4 4 3 3
## [1585] 3 5 4 4 4 2 3 3 3 3 3 2 2 3 3 3 3 3 2 2 8 9 6 6
## [1609] 6 7 6 6 7 6 6 7 7 1 3 4 2 2 2 2 2 2 5 5 5 5 3 3
## [1633] 3 3 5 3 3 3 3 3 3 3 3 2 2 2 2 5 4 4 4 4 4 3 5 5
## [1657] 5 5 5 5 5 5 2 2 4 4 6 8 5 6 5 7 5 5 6 5 5 6 5 3
## [1681] 4 2 2 2 2 2 2 5 5 5 4 3 4 3 3 5 3 3 3 3 3 3 3 3
## [1705] 2 2 2 2 5 4 4 4 3 3 3 5 4 5 4 4 5 5 5 2 1 4 4 6
## [1729] 7 5 6 5 6 5 5 6 5 5 6 5 5 4 5 5 5 5 3 7 7 7 5 6
## [1753] 6 5 5 6 1 1 1 5 5 5 5 5 4 2 2 2 7 6 6 7 5 5 6 6
## [1777] 5 6 5 5 5 6 6 5 4 4 4 9 10 8 8 8 9 8 7 8 8 8 8 8
## [1801] 5 5 5 5 5 3 3 3 4 2 6 6 6 6 2 5 5 6 5 6 6 5 5 6
## [1825] 5 5 5 4 3 3 3 2 2 3 1 1 2 1 1 1 2 2 4 3 2 2 8 9
## [1849] 6 6 6 7 7 7 7 7 7 7 7 1 1 1 1 3 5 5 5 5 2 2 2 2
## [1873] 5 4 4 4 1 2 2 1 1 2 3 3 3 5 4 4 4 4 3 3 5 5 6 5
## [1897] 5 5 6 6 2 2 5 5 5 6 4 4 4 5 4 3 4 4 4 4 4 1 1 1
## [1921] 3 5 5 5 6 2 2 1 1 6 4 4 5 1 1 1 1 1 1 3 3 3 5 4
## [1945] 4 4 4 4 3 6 6 6 6 6 6 6 6 2 2 5 6 4 6 4 4 4 5 4
## [1969] 3 4 3 3 4 4 1 1 4 6 6 5 6 1 2 1 1 6 4 4 4 1 1 1
## [1993] 1 1 1 3 3 3 5 5 4 5 5 4 3 6 6 7 6 6 6 6 6 2 2 6
## [2017] 6 4 6 4 4 4 5 4 3 4 3 4 4 4 1 3 6 6 5 6 1 2 1 1
## [2041] 6 4 4 4 1 1 1 1 1 1 3 3 3 5 4 4 4 4 4 3 6 6 6 6
## [2065] 6 6 6 6 2 2 6 6 4 6 4 4 4 5 4 3 4 3 4 4 4 3 6 6
## [2089] 5 6 1 2 1 1 6 4 4 4 1 1 1 1 1 1 3 3 3 5 4 4 4 4
## [2113] 4 3 6 6 6 6 6 6 6 6 2 2 6 6 4 6 4 4 4 5 4 3 4 3
## [2137] 4 4 4 5 5 5 4 4 5 4 4 4 3 3 3 4 4 4 4 4 3 2 2 2
## [2161] 5 4 4 4 3 3 3 4 4 4 4 4 4 4 4 3 2 3 3 7 8 6 6 6
## [2185] 7 6 6 7 6 6 7 6 1 2 4 6 7 6 6 2 7 7 8 6 6 6 6 6
## [2209] 6 6 6 6 2 2 2 2 2 2 3 3 3 3 4 4 3 3 3 4 4 4 5 7
## [2233] 8 4 5 5 6 6 6 6 6 6 7 7 1 4 6 6 6 6 2 8 8 8 6 6
## [2257] 6 5 5 6 6 7 6 2 2 2 2 2 2 3 3 3 4 4 4 3 3 4 4 4
## [2281] 5 5 7 8 4 5 5 6 5 6 6 6 6 6 6 5 6 6 6 6 3 8 8 8
## [2305] 5 5 5 5 5 6 6 7 7 1 2 2 1 3 3 3 4 4 5 5 5 4 4 4
## [2329] 4 4 5 6 6 7 3 4 4 5 5 5 5 5 5 5 6 7 7 7 7 3 6 6
## [2353] 6 6 7 7 6 6 6 5 5 5 5 4 4 4 3 4 4 2 1 1 1 1 1 1
## [2377] 1 5 4 1 2 9 10 7 8 8 9 8 8 9 8 8 9 8 1 1 1 7 5 5
## [2401] 5 1 1 1 1 1 2 4 4 4 6 5 5 5 5 5 4 7 7 7 7 7 7 7
## [2425] 7 3 3 7 7 3 5 4 4 4 5 3 3 4 3 3 3 3 1 1 7 5 5 5
## [2449] 1 1 1 2 2 2 4 4 4 6 5 5 5 6 5 4 7 7 8 7 7 7 7 7
## [2473] 3 3 7 7 3 5 4 4 4 5 3 3 4 3 3 3 3 1 6 5 5 5 1 1
## [2497] 1 1 1 2 4 4 4 5 5 5 5 5 4 4 7 7 7 7 7 7 7 7 3 3
## [2521] 6 7 4 5 4 4 4 5 3 3 4 3 3 3 3 7 5 5 5 1 1 1 1 1
## [2545] 2 3 4 4 5 5 5 5 5 5 4 7 7 7 7 7 7 7 7 3 3 6 7 4
## [2569] 5 4 4 4 5 3 3 4 3 3 3 3 7 7 7 6 6 6 6 6 6 6 6 6
## [2593] 3 3 3 3 2 2 3 1 2 2 2 2 2 2 2 4 4 3 4 8 9 6 6 6
## [2617] 7 7 7 7 7 7 7 7 1 1 5 5 5 5 5 4 2 2 2 7 7 7 7 6
## [2641] 6 6 6 6 6 6 6 6 6 6 5 4 5 5 8 10 7 8 8 9 7 7 8 7
## [2665] 7 8 7 1 5 5 5 5 5 4 2 2 2 7 7 7 7 6 6 6 6 6 6 6
## [2689] 6 6 6 6 5 4 5 5 8 10 7 8 8 9 8 7 8 7 7 8 7 5 5 5
## [2713] 5 5 4 2 2 2 8 7 7 7 6 6 6 6 6 6 6 6 6 6 6 5 4 5
## [2737] 5 8 10 7 8 8 9 8 7 8 7 7 8 8 1 1 1 1 2 3 4 3 5 4
## [2761] 4 4 5 4 3 6 6 7 6 6 6 6 6 2 3 6 6 4 5 4 4 4 5 3
## [2785] 3 4 3 3 4 3 1 1 1 2 3 4 4 5 4 4 4 5 4 3 6 6 7 6
## [2809] 6 6 7 7 3 3 6 6 4 5 3 4 4 5 3 3 4 3 3 3 3 1 1 2
## [2833] 3 4 4 5 4 4 4 5 4 3 6 6 7 6 6 6 7 7 3 3 6 6 4 5
## [2857] 3 4 4 5 3 3 4 3 3 3 3 1 2 3 3 3 5 4 4 4 4 4 3 6
## [2881] 6 6 6 6 6 6 6 2 2 6 6 4 6 3 4 4 5 3 3 4 3 3 4 3
## [2905] 2 3 4 3 5 4 4 4 4 4 3 6 6 6 6 6 6 6 6 2 2 6 6 4
## [2929] 5 3 4 4 5 3 3 4 3 3 4 3 2 3 3 6 5 5 5 5 4 4 6 6
## [2953] 7 6 6 6 7 7 3 3 6 6 5 6 5 5 5 6 4 4 5 4 4 5 4 1
## [2977] 1 6 5 5 5 5 4 4 6 5 6 5 5 6 6 6 3 3 5 4 7 8 6 7
## [3001] 6 7 6 5 6 6 6 6 6 1 6 6 5 6 5 5 4 6 5 6 5 5 6 6
## [3025] 6 3 3 4 4 7 8 6 7 7 8 6 6 7 6 6 7 6 6 5 5 6 5 5
## [3049] 4 6 5 6 5 5 6 6 6 3 3 4 4 7 8 6 7 6 8 6 6 7 6 6
## [3073] 6 6 1 1 1 3 2 2 4 4 5 4 5 4 4 4 4 4 5 6 6 7 3 4
## [3097] 4 5 5 5 5 5 5 5 5 1 1 2 2 2 4 4 4 4 4 4 4 4 3 3
## [3121] 4 5 6 7 3 4 4 5 4 5 5 5 5 5 5 1 2 2 2 4 4 4 4 4
## [3145] 4 4 4 3 3 4 5 6 6 3 4 4 5 4 4 5 4 4 5 5 2 2 2 4
## [3169] 4 4 4 4 4 4 4 3 3 4 5 6 7 3 4 4 5 4 4 5 5 5 5 5
## [3193] 1 2 2 2 3 3 3 2 2 3 3 3 3 4 7 8 4 5 5 6 6 5 6 6
## [3217] 6 6 6 1 3 3 3 3 3 3 3 3 2 2 3 4 6 7 4 5 5 6 5 5
## [3241] 6 5 5 6 6 4 4 4 4 4 4 4 4 2 2 4 5 5 6 3 4 4 5 4
## [3265] 4 5 4 4 5 5 1 1 1 1 1 1 1 4 4 2 3 9 10 6 7 7 8 7
## [3289] 7 8 7 7 8 8 1 1 1 1 1 1 4 4 2 3 9 10 6 7 7 8 7 7
## [3313] 8 7 7 8 8 1 1 1 1 1 5 5 2 3 9 10 7 7 7 8 8 8 8 8
## [3337] 8 9 8 1 1 1 1 4 4 1 2 9 10 6 7 7 8 8 7 8 8 8 8 8
## [3361] 1 1 1 4 4 1 2 9 10 7 7 7 8 8 7 8 8 8 8 8 1 1 4 4
## [3385] 2 3 9 10 6 7 7 8 7 7 8 7 7 8 8 1 5 4 2 3 9 10 6 7
## [3409] 7 8 8 7 8 8 8 8 8 5 4 2 3 9 10 6 7 7 8 8 7 8 8 8
## [3433] 8 8 1 4 5 5 6 3 4 4 5 4 4 5 4 4 5 4 4 4 6 7 4 5
## [3457] 4 6 4 4 5 4 4 5 5 1 9 10 7 7 7 8 8 7 8 8 8 8 8 9
## [3481] 10 7 8 8 9 8 8 9 8 8 9 9 2 4 3 3 3 2 2 2 2 2 1 1
## [3505] 4 3 3 3 3 3 2 3 3 2 3 1 1 2 2 2 2 2 2 3 3 1 1 2
## [3529] 2 2 2 2 2 3 2 1 2 2 2 2 2 2 2 3 2 3 2 2 3 1 1 1
## [3553] 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## Levels: 1 2 3 4 5 6 7 8 9 10
aquifer_pair$to
## [1] 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## [25] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
## [49] 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
## [73] 74 75 76 77 78 79 80 81 82 83 84 85 3 4 5 6 7 8 9 10 11 12 13 14
## [97] 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
## [121] 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62
## [145] 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 4
## [169] 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
## [193] 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## [217] 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## [241] 77 78 79 80 81 82 83 84 85 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
## [265] 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
## [289] 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
## [313] 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 6 7 8 9 10 11
## [337] 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
## [361] 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59
## [385] 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83
## [409] 84 85 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
## [433] 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## [457] 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## [481] 77 78 79 80 81 82 83 84 85 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
## [505] 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
## [529] 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
## [553] 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 9 10 11 12 13 14 15 16 17
## [577] 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
## [601] 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
## [625] 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 10 11 12 13
## [649] 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
## [673] 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
## [697] 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [721] 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
## [745] 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
## [769] 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
## [793] 83 84 85 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
## [817] 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
## [841] 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## [865] 81 82 83 84 85 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
## [889] 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55
## [913] 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
## [937] 80 81 82 83 84 85 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
## [961] 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55
## [985] 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
## [1009] 80 81 82 83 84 85 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
## [1033] 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
## [1057] 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## [1081] 81 82 83 84 85 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
## [1105] 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
## [1129] 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
## [1153] 83 84 85 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
## [1177] 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
## [1201] 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [1225] 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
## [1249] 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
## [1273] 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 19 20 21 22
## [1297] 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
## [1321] 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
## [1345] 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 20 21 22 23 24 25 26 27 28
## [1369] 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## [1393] 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## [1417] 77 78 79 80 81 82 83 84 85 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
## [1441] 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59
## [1465] 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83
## [1489] 84 85 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
## [1513] 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
## [1537] 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 23 24 25 26 27 28
## [1561] 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## [1585] 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## [1609] 77 78 79 80 81 82 83 84 85 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
## [1633] 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62
## [1657] 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 25
## [1681] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
## [1705] 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
## [1729] 74 75 76 77 78 79 80 81 82 83 84 85 26 27 28 29 30 31 32 33 34 35 36 37
## [1753] 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
## [1777] 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [1801] 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
## [1825] 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
## [1849] 75 76 77 78 79 80 81 82 83 84 85 28 29 30 31 32 33 34 35 36 37 38 39 40
## [1873] 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
## [1897] 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 29 30 31
## [1921] 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55
## [1945] 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
## [1969] 80 81 82 83 84 85 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
## [1993] 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
## [2017] 72 73 74 75 76 77 78 79 80 81 82 83 84 85 31 32 33 34 35 36 37 38 39 40
## [2041] 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
## [2065] 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 32 33 34
## [2089] 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
## [2113] 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
## [2137] 83 84 85 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53
## [2161] 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77
## [2185] 78 79 80 81 82 83 84 85 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
## [2209] 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
## [2233] 74 75 76 77 78 79 80 81 82 83 84 85 35 36 37 38 39 40 41 42 43 44 45 46
## [2257] 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
## [2281] 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 36 37 38 39 40 41 42 43 44
## [2305] 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68
## [2329] 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 37 38 39 40 41 42 43
## [2353] 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
## [2377] 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 38 39 40 41 42 43
## [2401] 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
## [2425] 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 39 40 41 42 43 44
## [2449] 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68
## [2473] 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 40 41 42 43 44 45 46
## [2497] 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
## [2521] 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 41 42 43 44 45 46 47 48 49
## [2545] 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
## [2569] 74 75 76 77 78 79 80 81 82 83 84 85 42 43 44 45 46 47 48 49 50 51 52 53
## [2593] 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77
## [2617] 78 79 80 81 82 83 84 85 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
## [2641] 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
## [2665] 83 84 85 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
## [2689] 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 45 46 47
## [2713] 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71
## [2737] 72 73 74 75 76 77 78 79 80 81 82 83 84 85 46 47 48 49 50 51 52 53 54 55
## [2761] 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
## [2785] 80 81 82 83 84 85 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
## [2809] 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 48 49 50
## [2833] 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
## [2857] 75 76 77 78 79 80 81 82 83 84 85 49 50 51 52 53 54 55 56 57 58 59 60 61
## [2881] 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [2905] 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
## [2929] 74 75 76 77 78 79 80 81 82 83 84 85 51 52 53 54 55 56 57 58 59 60 61 62
## [2953] 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 52
## [2977] 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## [3001] 77 78 79 80 81 82 83 84 85 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
## [3025] 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 54 55 56 57 58 59
## [3049] 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83
## [3073] 84 85 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## [3097] 77 78 79 80 81 82 83 84 85 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
## [3121] 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 57 58 59 60 61 62 63 64 65
## [3145] 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 58 59 60 61
## [3169] 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [3193] 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
## [3217] 83 84 85 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## [3241] 81 82 83 84 85 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
## [3265] 80 81 82 83 84 85 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79
## [3289] 80 81 82 83 84 85 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## [3313] 81 82 83 84 85 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
## [3337] 83 84 85 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
## [3361] 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 67 68 69 70
## [3385] 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 68 69 70 71 72 73 74 75 76
## [3409] 77 78 79 80 81 82 83 84 85 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83
## [3433] 84 85 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 71 72 73 74 75 76
## [3457] 77 78 79 80 81 82 83 84 85 72 73 74 75 76 77 78 79 80 81 82 83 84 85 73
## [3481] 74 75 76 77 78 79 80 81 82 83 84 85 74 75 76 77 78 79 80 81 82 83 84 85
## [3505] 75 76 77 78 79 80 81 82 83 84 85 76 77 78 79 80 81 82 83 84 85 77 78 79
## [3529] 80 81 82 83 84 85 78 79 80 81 82 83 84 85 79 80 81 82 83 84 85 80 81 82
## [3553] 83 84 85 81 82 83 84 85 82 83 84 85 83 84 85 84 85 85
aquifer.v<-est.variogram(aquifer_points,aquifer_pair,'resi')
g4=ggplot(aquifer, aes(resi, Este)) +
geom_point() +
geom_line() +
xlab("Este") +
ylab("residuales2")
g5=ggplot(aquifer, aes(resi, Norte)) +
geom_point() +
geom_line() +
xlab("Norte") +
ylab("residuales2")
plot_grid(g4,g5)
aquifer_points=point(aquifer, x="Este", y="Norte")
fit.trend(aquifer_points,at="Profundidad", np=2, plot.it=TRUE)
## $beta
## x^0 y^0 x^1 y^0 x^2 y^0 x^0 y^1 x^1 y^1
## 2.481430e+03 -8.373708e+00 1.416675e-03 -2.043419e+00 2.680056e-02
## x^0 y^2
## -2.464371e-02
##
## $R
## x^0 y^0 x^1 y^0 x^2 y^0 x^0 y^1 x^1 y^1 x^0 y^2
## [1,] -9.219544 -155.6739 -41051.636 -731.67314 -16082.944 -85540.31
## [2,] 0.000000 595.1832 3500.219 57.75539 38829.771 12491.66
## [3,] 0.000000 0.0000 39397.313 -117.36878 1909.315 -23722.80
## [4,] 0.000000 0.0000 0.000 485.98967 14332.040 91118.22
## [5,] 0.000000 0.0000 0.000 0.00000 25401.055 3240.90
## [6,] 0.000000 0.0000 0.000 0.00000 0.000 19989.20
##
## $np
## [1] 2
##
## $x
## [1] 42.78275 -27.39691 -1.16289 -18.61823 96.46549 108.56243
## [7] 88.36356 90.04213 93.17269 97.61099 90.62946 92.55262
## [13] 99.48996 -24.06744 -26.06285 56.27842 73.03881 80.26679
## [19] 80.23009 68.83845 76.39921 64.46148 43.39657 39.07769
## [25] 112.80450 54.25899 6.13202 -3.80469 -2.23054 -2.36177
## [31] -2.18890 63.22428 -10.77860 -18.98889 -38.57884 83.14496
## [37] -21.80248 -23.56457 -20.11299 -16.62654 29.90748 100.91568
## [43] 101.29544 103.26625 -14.31073 -18.13447 -18.12151 -9.88796
## [49] -12.16336 11.65754 61.69122 69.57896 66.72205 -36.65446
## [55] -19.55102 -21.29791 -22.36166 21.14719 7.68461 -8.33227
## [61] 56.70724 59.00052 68.96893 70.90225 73.00243 59.66237
## [67] 61.87249 63.70810 5.62706 18.24739 85.68824 105.07646
## [73] -101.64278 -145.23654 -73.99313 -94.48182 -88.84983 -120.25898
## [79] -86.02454 -72.79097 -100.17372 -78.83539 -83.69063 -95.61661
## [85] -87.55480
##
## $y
## [1] 127.62282 90.78732 84.89600 76.45199 64.58058 82.92325 56.45348
## [8] 39.25820 33.05852 56.27887 35.08169 41.75238 59.15785 184.76636
## [15] 114.07479 26.84826 18.88140 12.61593 14.61795 107.77423 95.99380
## [22] 110.39641 53.61499 61.99805 45.54766 147.81987 48.32772 40.40450
## [29] 29.91113 33.82002 33.68207 79.49924 175.11346 171.91695 158.52742
## [36] 159.11559 15.02551 9.41441 22.09269 17.25621 175.12875 22.97808
## [43] 22.96385 20.34239 31.26545 30.18118 29.53241 38.14483 39.11081
## [50] 18.73347 32.94906 33.80841 33.93264 150.91457 137.78404 131.82542
## [57] 137.13680 139.26199 126.83751 107.77691 171.26443 164.54863 177.24820
## [64] 161.38136 162.98959 170.10544 174.30177 173.91454 79.08730 77.39191
## [71] 139.81702 132.03181 10.65106 28.02333 87.97270 86.62606 76.70991
## [78] 80.76485 54.36334 43.09215 42.89881 40.82141 46.50482 35.82183
## [85] 29.39267
##
## $z
## [1] 1464 2553 2158 2455 1756 1702 1805 1797 1714 1466 1729 1638 1736 1476 2200
## [16] 1999 1680 1806 1682 1306 1722 1437 1828 2118 1725 1606 2648 2560 2544 2386
## [31] 2400 1757 1402 1364 1735 1376 2729 2766 2736 2432 1024 1611 1548 1591 2540
## [46] 2352 2528 2575 2468 2646 1739 1674 1868 1865 1777 1579 1771 1408 1527 2003
## [61] 1386 1089 1384 1030 1092 1161 1415 1231 2300 2238 1038 1332 3510 3490 2594
## [76] 2650 2533 3571 2811 2728 3136 2553 2798 2691 2946
##
## $residuals
## [1] -145.932017 296.391955 20.569629 155.586776 136.944207 210.578982
## [7] 112.643763 81.535500 12.407325 -165.733666 11.643984 -55.843867
## [13] 123.038140 130.250727 132.838620 16.473072 -186.973641 -9.864104
## [19] -133.020821 -298.072286 98.737035 -175.328351 -174.667016 118.113364
## [25] 176.632628 200.333264 366.232978 173.604750 128.842139 -15.778284
## [31] -1.005758 -17.176812 -5.743382 -109.803640 35.578021 175.509274
## [37] 109.375693 113.827801 154.658230 -138.758151 -234.947039 -41.999962
## [43] -102.169175 -45.349545 38.415648 -182.959426 -9.456222 134.544149
## [49] 14.873572 303.070200 -191.631118 -197.446346 -23.989926 92.632496
## [55] -47.092725 -308.538280 -72.511843 -213.402614 -260.643390 -17.741523
## [61] 187.380986 -159.999448 282.152142 -199.908135 -116.838018 -37.190026
## [67] 262.093246 81.109636 169.467368 176.796541 -289.932780 42.387375
## [73] 216.381585 -51.786437 30.159248 -53.946573 -219.188525 648.160187
## [79] -92.004756 -152.583829 49.711612 -386.649271 -141.519561 -407.429504
## [85] -129.126052
##
## attr(,"class")
## [1] "trend.surface"
g6=ggplot(aquifer.v, aes(resi, Norte)) +
geom_point() +
geom_line() +
xlab("Norte") +
ylab("residuales2")
g6=ggplot(aquifer.v, aes(bins, classic)) +
geom_point() +
geom_line() +
xlab("Rezago espacial, h") +
ylab("Estimador clásico del variograma")
g7=ggplot(aquifer.v, aes(bins, robust)) +
geom_point() +
geom_line() +
xlab("Rezago espacial, h") +
ylab("Estimador robusto 1 del variograma")
g8=ggplot(aquifer.v, aes(bins, med)) +
geom_point() +
geom_line() +
xlab("Rezago espacial, h") +
ylab("Estimador robusto 2 del variograma")
plot_grid(g6,g7,g8,nrow=1,ncol=3)
#par(mfrow=c(1,3))
plot(aquifer.v)
plot(aquifer.v$robust)
plot(aquifer.v$med)
#points(aquifer.v$robust,col="red")
#points(aquifer.v$med,"blue")
aquifer.vmodExp<-fit.exponential(aquifer.v,c0=0,ce=40000,ae=20,plot.it=TRUE,iterations=30)
## Initial parameter estimates: 0 40000 20
## Iteration: 1
## Gradient vector: -4432.441 977.0988 -8.943538
## New parameter estimates: 1e-06 40977.1 11.05646
##
## rse.dif = 3232643827 (rse = 3232643827 ) ; parm.dist = 977.1397
## Iteration: 2
## Gradient vector: -26700.7 22493.46 -2.800242
## New parameter estimates: 1e-06 63470.56 8.256219
##
## rse.dif = -17644208 (rse = 3.215e+09 ) ; parm.dist = 22493.46
## Iteration: 3
## Gradient vector: -11057.27 -15597.73 2.315183
## New parameter estimates: 1e-06 47872.83 10.5714
##
## rse.dif = -3772568 (rse = 3211227051 ) ; parm.dist = 15597.73
## Iteration: 4
## Gradient vector: -27525.12 16431.58 -1.824505
## New parameter estimates: 1e-06 64304.41 8.746897
##
## rse.dif = 3032851 (rse = 3214259902 ) ; parm.dist = 16431.58
## Iteration: 5
## Gradient vector: -20442.22 -7053.019 1.144197
## New parameter estimates: 1e-06 57251.39 9.891094
##
## rse.dif = -2468665 (rse = 3211791237 ) ; parm.dist = 7053.019
## Iteration: 6
## Gradient vector: -27557.41 7097.539 -0.7122805
## New parameter estimates: 1e-06 64348.93 9.178813
##
## rse.dif = 1486180 (rse = 3213277417 ) ; parm.dist = 7097.539
## Iteration: 7
## Gradient vector: -24787.06 -2758.919 0.3605893
## New parameter estimates: 1e-06 61590.01 9.539403
##
## rse.dif = -951749.7 (rse = 3212325667 ) ; parm.dist = 2758.919
## Iteration: 8
## Gradient vector: -26691.4 1898.737 -0.1885371
## New parameter estimates: 1e-06 63488.75 9.350866
##
## rse.dif = 471370.4 (rse = 3212797038 ) ; parm.dist = 1898.737
## Iteration: 9
## Gradient vector: -25850.35 -838.0686 0.09276125
## New parameter estimates: 1e-06 62650.68 9.443627
##
## rse.dif = -249219.6 (rse = 3212547818 ) ; parm.dist = 838.0686
## Iteration: 10
## Gradient vector: -26302.53 450.7265 -0.04631475
## New parameter estimates: 1e-06 63101.41 9.397312
##
## rse.dif = 121873.4 (rse = 3212669692 ) ; parm.dist = 450.7265
## Iteration: 11
## Gradient vector: -26086.54 -215.2624 0.02285916
## New parameter estimates: 1e-06 62886.14 9.420171
##
## rse.dif = -61031.79 (rse = 3212608660 ) ; parm.dist = 215.2624
## Iteration: 12
## Gradient vector: -26195.52 108.6221 -0.01133309
## New parameter estimates: 1e-06 62994.77 9.408838
##
## rse.dif = 30077.83 (rse = 3212638738 ) ; parm.dist = 108.6221
## Iteration: 13
## Gradient vector: -26142.08 -53.26613 0.005604603
## New parameter estimates: 1e-06 62941.5 9.414443
##
## rse.dif = -14922.96 (rse = 3212623815 ) ; parm.dist = 53.26613
## Iteration: 14
## Gradient vector: -26168.65 26.48517 -0.002774911
## New parameter estimates: 1e-06 62967.99 9.411668
##
## rse.dif = 7377.216 (rse = 3212631192 ) ; parm.dist = 26.48517
## Iteration: 15
## Gradient vector: -26155.53 -13.07801 0.001373075
## New parameter estimates: 1e-06 62954.91 9.413041
##
## rse.dif = -3653.216 (rse = 3212627539 ) ; parm.dist = 13.07801
## Iteration: 16
## Gradient vector: -26162.03 6.479831 -0.0006796194
## New parameter estimates: 1e-06 62961.39 9.412361
##
## rse.dif = 1807.514 (rse = 3212629346 ) ; parm.dist = 6.479831
## Iteration: 17
## Gradient vector: -26158.82 -3.20516 0.0003363367
## New parameter estimates: 1e-06 62958.18 9.412698
##
## rse.dif = -894.6895 (rse = 3212628451 ) ; parm.dist = 3.20516
## Iteration: 18
## Gradient vector: -26160.41 1.586717 -0.0001664615
## New parameter estimates: 1e-06 62959.77 9.412531
##
## rse.dif = 442.763 (rse = 3212628894 ) ; parm.dist = 1.586717
## Iteration: 19
## Gradient vector: -26159.62 -0.7851797 8.238305e-05
## New parameter estimates: 1e-06 62958.98 9.412613
##
## rse.dif = -219.1369 (rse = 3212628675 ) ; parm.dist = 0.7851797
## Iteration: 20
## Gradient vector: -26160.01 0.3886224 -4.077272e-05
## New parameter estimates: 1e-06 62959.37 9.412573
##
## rse.dif = 108.4519 (rse = 3212628784 ) ; parm.dist = 0.3886224
## Iteration: 21
## Gradient vector: -26159.82 -0.192328 2.017891e-05
## New parameter estimates: 1e-06 62959.18 9.412593
##
## rse.dif = -53.67477 (rse = 3212628730 ) ; parm.dist = 0.192328
## Iteration: 22
## Gradient vector: -26159.91 0.09518727 -9.986825e-06
## New parameter estimates: 1e-06 62959.28 9.412583
##
## rse.dif = 26.56425 (rse = 3212628756 ) ; parm.dist = 0.09518727
## Iteration: 23
## Gradient vector: -26159.86 -0.04710907 4.942611e-06
## New parameter estimates: 1e-06 62959.23 9.412588
##
## rse.dif = -13.14703 (rse = 3212628743 ) ; parm.dist = 0.04710907
## Iteration: 24
## Gradient vector: -26159.89 0.02331501 -2.446166e-06
## New parameter estimates: 1e-06 62959.25 9.412585
##
## rse.dif = 6.506637 (rse = 3212628750 ) ; parm.dist = 0.02331501
## Iteration: 25
## Gradient vector: -26159.88 -0.01153889 1.21064e-06
## New parameter estimates: 1e-06 62959.24 9.412587
##
## rse.dif = -3.220223 (rse = 3212628747 ) ; parm.dist = 0.01153889
## Iteration: 26
## Gradient vector: -26159.88 0.005710766 -5.991629e-07
## New parameter estimates: 1e-06 62959.25 9.412586
##
## rse.dif = 1.593733 (rse = 3212628748 ) ; parm.dist = 0.005710766
## Iteration: 27
## Gradient vector: -26159.88 -0.002826337 2.965342e-07
## New parameter estimates: 1e-06 62959.24 9.412586
##
## rse.dif = -0.7887607 (rse = 3212628747 ) ; parm.dist = 0.002826337
## Iteration: 28
## Gradient vector: -26159.88 0.001398792 -1.467587e-07
## New parameter estimates: 1e-06 62959.24 9.412586
##
## rse.dif = 0.390368 (rse = 3212628748 ) ; parm.dist = 0.001398792
## Iteration: 29
## Gradient vector: -26159.88 -0.0006922786 7.263263e-08
## New parameter estimates: 1e-06 62959.24 9.412586
##
## rse.dif = -0.1931987 (rse = 3212628748 ) ; parm.dist = 0.0006922786
## Iteration: 30
## Gradient vector: -26159.88 0.0003426161 -3.594667e-08
## New parameter estimates: 1e-06 62959.24 9.412586
##
## rse.dif = 0.09561539 (rse = 3212628748 ) ; parm.dist = 0.0003426161
## Convergence not achieved!
aquifer.vmodGau<-fit.gaussian(aquifer.v,c0=0,cg=50000,ag=50,plot.it=TRUE,iterations=30)
## Initial parameter estimates: 0 50000 50
## Iteration: 1
## Gradient vector: 19162.34 -33401.14 -11.41191
## New parameter estimates: 19162.34 16598.86 38.58809
##
## rse.dif = 3299750048 (rse = 3299750048 ) ; parm.dist = 38507.55
## Iteration: 2
## Gradient vector: -1294.927 2010.017 -18.77473
## New parameter estimates: 17867.41 18608.87 19.81336
##
## rse.dif = -66430135 (rse = 3233319913 ) ; parm.dist = 2391.1
## Iteration: 3
## Gradient vector: 3201.043 -2835.169 9.216254
## New parameter estimates: 21068.46 15773.71 29.02961
##
## rse.dif = -24694350 (rse = 3208625564 ) ; parm.dist = 4276.09
## Iteration: 4
## Gradient vector: -4345.272 4292.413 -6.361973
## New parameter estimates: 16723.18 20066.12 22.66764
##
## rse.dif = 4004881 (rse = 3212630445 ) ; parm.dist = 6107.884
## Iteration: 5
## Gradient vector: 53.88685 -4.270081 2.074271
## New parameter estimates: 16777.07 20061.85 24.74191
##
## rse.dif = -3703977 (rse = 3208926468 ) ; parm.dist = 54.09555
## Iteration: 6
## Gradient vector: -391.4471 384.4526 -0.5571294
## New parameter estimates: 16385.62 20446.3 24.18478
##
## rse.dif = 588163 (rse = 3209514631 ) ; parm.dist = 548.6666
## Iteration: 7
## Gradient vector: 29.55911 -27.0943 0.07968918
## New parameter estimates: 16415.18 20419.21 24.26447
##
## rse.dif = -201438.9 (rse = 3209313192 ) ; parm.dist = 40.09799
## Iteration: 8
## Gradient vector: -6.581211 6.259206 -0.01207028
## New parameter estimates: 16408.6 20425.47 24.2524
##
## rse.dif = 26607.8 (rse = 3209339800 ) ; parm.dist = 9.082408
## Iteration: 9
## Gradient vector: 0.9423146 -0.8928955 0.001794561
## New parameter estimates: 16409.54 20424.57 24.25419
##
## rse.dif = -4077.43 (rse = 3209335722 ) ; parm.dist = 1.298161
## Iteration: 10
## Gradient vector: -0.1413215 0.1339887 -0.0002673761
## New parameter estimates: 16409.4 20424.71 24.25393
##
## rse.dif = 605.1536 (rse = 3209336327 ) ; parm.dist = 0.194743
## Iteration: 11
## Gradient vector: 0.02102884 -0.01993597 3.982407e-05
## New parameter estimates: 16409.42 20424.69 24.25397
##
## rse.dif = -90.18701 (rse = 3209336237 ) ; parm.dist = 0.02897682
## Iteration: 12
## Gradient vector: -0.003132718 0.00296995 -5.931842e-06
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 13.43229 (rse = 3209336251 ) ; parm.dist = 0.004316777
## Iteration: 13
## Gradient vector: 0.0004666088 -0.0004423641 8.835486e-07
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = -2.000768 (rse = 3209336249 ) ; parm.dist = 0.0006429701
## Iteration: 14
## Gradient vector: -6.950174e-05 6.589049e-05 -1.316048e-07
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 0.2980156 (rse = 3209336249 ) ; parm.dist = 9.577091e-05
## Iteration: 15
## Gradient vector: 1.035231e-05 -9.814415e-06 1.960261e-08
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = -0.04438972 (rse = 3209336249 ) ; parm.dist = 1.426512e-05
## Iteration: 16
## Gradient vector: -1.541989e-06 1.461872e-06 -2.919836e-09
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 0.006611824 (rse = 3209336249 ) ; parm.dist = 2.124808e-06
## Iteration: 17
## Gradient vector: 2.29702e-07 -2.177649e-07 4.349504e-10
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = -0.0009841919 (rse = 3209336249 ) ; parm.dist = 3.165203e-07
## Iteration: 18
## Gradient vector: -3.42286e-08 3.244849e-08 -6.480716e-11
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 0.0001459122 (rse = 3209336249 ) ; parm.dist = 4.716456e-08
## Iteration: 19
## Gradient vector: 5.117361e-09 -4.848551e-09 9.688533e-12
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = -2.241135e-05 (rse = 3209336249 ) ; parm.dist = 7.051061e-09
## Iteration: 20
## Gradient vector: -7.696674e-10 7.270391e-10 -1.463951e-12
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 4.291534e-06 (rse = 3209336249 ) ; parm.dist = 1.060296e-09
## Iteration: 21
## Gradient vector: 1.036345e-10 -9.511823e-11 2.010728e-13
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = -1.430511e-06 (rse = 3209336249 ) ; parm.dist = 1.390071e-10
## Iteration: 22
## Gradient vector: -1.632815e-11 1.786392e-11 -3.703972e-14
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 1.430511e-06 (rse = 3209336249 ) ; parm.dist = 2.329446e-11
## Iteration: 23
## Gradient vector: -3.827252e-12 2.836377e-12 3.527592e-15
## New parameter estimates: 16409.42 20424.69 24.25396
##
## rse.dif = 0 (rse = 3209336249 ) ; parm.dist = 5.14488e-12
##
## Convergence achieved by sums of squares.
## Final parameter estimates: 16409.42 20424.69 24.25396
aquifer.vmodWave<-fit.wave(aquifer.v,c0=0,cw=40000,aw=10,plot.it=TRUE,iterations=30,weighted=T)
## Initial parameter estimates: 0 40000 10
## Iteration: 1
## Gradient vector: 18650.32 -21981.27 -0.7942028
## New parameter estimates: 18650.32 18018.73 9.205797
##
## rse.dif = 3409704989 (rse = 3409704989 ) ; parm.dist = 28827.26
## Iteration: 2
## Gradient vector: 812.9227 -1109.399 -1.187299
## New parameter estimates: 19463.25 16909.33 8.018498
##
## rse.dif = -289093760 (rse = 3120611230 ) ; parm.dist = 1375.358
## Iteration: 3
## Gradient vector: -6990.158 6973.566 0.9858099
## New parameter estimates: 12473.09 23882.9 9.004308
##
## rse.dif = 24044562 (rse = 3144655792 ) ; parm.dist = 9873.851
## Iteration: 4
## Gradient vector: 7025.438 -6960.473 -1.260353
## New parameter estimates: 19498.53 16922.43 7.743955
##
## rse.dif = -56767551 (rse = 3087888241 ) ; parm.dist = 9889.639
## Iteration: 5
## Gradient vector: -9210.154 9213.61 1.066674
## New parameter estimates: 10288.37 26136.04 8.810629
##
## rse.dif = 175986924 (rse = 3263875165 ) ; parm.dist = 13027.57
## Iteration: 6
## Gradient vector: 11994.7 -11983.26 -2.255679
## New parameter estimates: 22283.07 14152.77 6.55495
##
## rse.dif = -196728543 (rse = 3067146622 ) ; parm.dist = 16954.98
## Iteration: 7
## Gradient vector: -14060.45 14195.04 -1.578095
## New parameter estimates: 8222.625 28347.81 4.976855
##
## rse.dif = 147278852 (rse = 3214425474 ) ; parm.dist = 19979.87
## Iteration: 8
## Gradient vector: -15826.64 16212.91 0.3854677
## New parameter estimates: 1e-06 44560.72 5.362323
##
## rse.dif = -46983778 (rse = 3167441696 ) ; parm.dist = 18178.84
## Iteration: 9
## Gradient vector: 13145.08 -21444.98 -0.8756698
## New parameter estimates: 13145.08 23115.75 4.486653
##
## rse.dif = -757940879 (rse = 2409500817 ) ; parm.dist = 25153.13
## Iteration: 10
## Gradient vector: -9434763 9682459 25.73116
## New parameter estimates: 1e-06 9705575 30.21781
##
## rse.dif = 1636307005 (rse = 4045807822 ) ; parm.dist = 9682468
## Iteration: 11
## Gradient vector: 20962.2 -9688482 0.02156687
## New parameter estimates: 20962.2 17093.21 30.23938
##
## rse.dif = 83628062 (rse = 4129435883 ) ; parm.dist = 9688504
## Iteration: 12
## Gradient vector: 7173.136 -8587.116 1.22582
## New parameter estimates: 28135.34 8506.099 31.4652
##
## rse.dif = -628497356 (rse = 3500938527 ) ; parm.dist = 11188.94
## Iteration: 13
## Gradient vector: 2974.651 -2890.861 -4.19572
## New parameter estimates: 31109.99 5615.237 27.26947
##
## rse.dif = -192443200 (rse = 3308495327 ) ; parm.dist = 4147.969
## Iteration: 14
## Gradient vector: -2399.351 1443.698 15.69929
## New parameter estimates: 28710.64 7058.936 42.96876
##
## rse.dif = 147479203 (rse = 3455974530 ) ; parm.dist = 2800.25
## Iteration: 15
## Gradient vector: 4786.661 2165.107 -43.14322
## New parameter estimates: 33497.3 9224.042 1e-06
##
## rse.dif = -686128323 (rse = 2769846206 ) ; parm.dist = 5253.728
## Iteration: 16
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: -7188.309 -5.926894e-07 0
## New parameter estimates: 26308.99 9224.042 1e-06
##
## rse.dif = 686457465 (rse = 3456303671 ) ; parm.dist = 7188.309
## Iteration: 17
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: -5.339325e-06 -5.926894e-07 0
## New parameter estimates: 26308.99 9224.042 1e-06
##
## rse.dif = 0.4889326 (rse = 3456303672 ) ; parm.dist = 5.372118e-06
## Iteration: 18
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 5.926854e-07 -5.926894e-07 0
## New parameter estimates: 26308.99 9224.042 1e-06
##
## rse.dif = 2.384186e-06 (rse = 3456303672 ) ; parm.dist = 8.381857e-07
## Iteration: 19
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 5.926902e-07 -5.926894e-07 0
## New parameter estimates: 26308.99 9224.042 1e-06
##
## rse.dif = -1.907349e-06 (rse = 3456303672 ) ; parm.dist = 8.381882e-07
## Iteration: 20
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 5.926902e-07 -5.926894e-07 0
## New parameter estimates: 26308.99 9224.042 1e-06
##
## rse.dif = 0 (rse = 3456303672 ) ; parm.dist = 8.381882e-07
##
## Convergence achieved by sums of squares.
## Final parameter estimates: 26308.99 9224.042 1e-06
curve(65000*(1-(14/x)*sin(x/14)),0,300,ylim=c(0,200000))
points(aquifer.v$bins,aquifer.v$classic,col=3)
text(aquifer.v$bins,aquifer.v$classic,aquifer.v$n,col=2)
curve(200000*(1-exp(-x/170)),0,300)
points(aquifer.v$bins,aquifer.v$classic,col=2)
curve(65000*(1-(14/x)*sin(x/14)),0,300,ylim=c(0,200000))
points(aquifer.v$bins,aquifer.v$classic,col=3)
text(aquifer.v$bins,aquifer.v$classic,aquifer.v$n,col=2)
aquifer.vmodExp<-fit.exponential(aquifer.v,c0=0,ce=200000,ae=170,plot.it=TRUE,iterations=30,weighted=T)
## Initial parameter estimates: 0 2e+05 170
## Iteration: 1
## Gradient vector: 16365.66 -238859.4 -103.7436
## New parameter estimates: 16365.66 1e-06 66.25643
##
## rse.dif = 3826411368 (rse = 3826411368 ) ; parm.dist = 200668.5
## Iteration: 2
## Gradient vector: 7737.246 16547.95 166070861252
## New parameter estimates: 24102.91 16547.95 166070861318
##
## rse.dif = -767474321 (rse = 3058937047 ) ; parm.dist = 166070861252
## Iteration: 3
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 3355.03 1.242479e+13 0
## New parameter estimates: 27457.94 1.242479e+13 166070861318
##
## rse.dif = -120011141 (rse = 2938925906 ) ; parm.dist = 1.242479e+13
## Iteration: 4
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 423.3165 -663474885968 0
## New parameter estimates: 27881.25 1.176131e+13 166070861318
##
## rse.dif = 11801483 (rse = 2950727388 ) ; parm.dist = 663474885968
## Iteration: 5
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 3.873181 -6320523090 0
## New parameter estimates: 27885.12 1.175499e+13 166070861318
##
## rse.dif = 128956.4 (rse = 2950856345 ) ; parm.dist = 6320523090
## Iteration: 6
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 0.02266712 -36921321 0
## New parameter estimates: 27885.15 1.175495e+13 166070861318
##
## rse.dif = 752.3639 (rse = 2950857097 ) ; parm.dist = 36921321
## Iteration: 7
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 0.0001316946 -214507.3 0
## New parameter estimates: 27885.15 1.175495e+13 166070861318
##
## rse.dif = 4.371067 (rse = 2950857102 ) ; parm.dist = 214507.3
## Iteration: 8
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 7.651061e-07 -1246.218 0
## New parameter estimates: 27885.15 1.175495e+13 166070861318
##
## rse.dif = 0.02539396 (rse = 2950857102 ) ; parm.dist = 1246.217
## Iteration: 9
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 4.444639e-09 -7.24441 0
## New parameter estimates: 27885.15 1.175495e+13 166070861318
##
## rse.dif = 0.0001482964 (rse = 2950857102 ) ; parm.dist = 7.244141
## Iteration: 10
## Warning in lsfit(xmat, y, wt = w, intercept = FALSE): 'X' matrix was collinear
## Gradient vector: 2.418472e-11 -0.03727549 0
## New parameter estimates: 27885.15 1.175495e+13 166070861318
##
## rse.dif = 9.536743e-07 (rse = 2950857102 ) ; parm.dist = 0.03710938
##
## Convergence achieved by sums of squares.
## Final parameter estimates: 27885.15 1.175495e+13 166070861318
aquifer.vmodwave<-fit.wave(aquifer.v,c0=4000,cw=30000,aw=15,plot.it=TRUE,iterations=0,weighted=T)
## Convergence not achieved!
aquifer.vmodExp_0<-fit.exponential(aquifer.v,c0=0,ce=200000,ae=170,plot.it=TRUE,iterations=0,weighted=T)
## Convergence not achieved!
aquifer.vmodwave_0<-fit.wave(aquifer.v,c0=4000,cw=30000,aw=15,plot.it=TRUE,iterations=0,weighted=T)
## Convergence not achieved!
aquifer.spherical<-fit.spherical(aquifer.v,c0=0,cs=35000,as=70,plot.it=TRUE,iterations=0,weighted=T)
## Convergence not achieved!
ggplot(aquifer.v, aes(bins, classic)) +
geom_point() +
geom_line() +
xlab("Rezago espacial, h") +
ylab("Estimador clásico del variograma")+
xlim(0, 300) +
geom_function(aes(color = "Exponencial"),
fun =~4000+150000*(1-exp(-.x/100))
) +
geom_function(aes(color = "Seno cardinal"),
fun =~4000+30000*(1-((15/.x)*sin(.x/15)))
) + xlab("Rezago espacial") + ylab("Modelos teóricos de semivariogramas")
## Warning: Removed 1 row(s) containing missing values (geom_path).
Kriging_aquifer <- point(data.frame(list(x=10,y=80)))
Kriging_aquifer <- krige(Kriging_aquifer, aquifer_points, 'resi', aquifer.vmodExp_0)
##
## Using all points.
## Preparing the kriging system matrix...
## Inverting the matrix...
## Predicting.
Kriging_aquifer
##
## Point object: x
##
## Locations: 1
##
## Attributes:
## x
## y
## do
## zhat
## sigma2hat
Kriging_aquifer$zhat
## [1] 222.4383
Kriging_aquifer$sigma2hat
## [1] 7010.452
Kriging_aquifer <- point(data.frame(list(x=10,y=80)))
Kriging_aquifer <- krige(Kriging_aquifer, aquifer_points, 'resi', aquifer.vmodwave_0)
##
## Using all points.
## Preparing the kriging system matrix...
## Inverting the matrix...
## Predicting.
Kriging_aquifer
##
## Point object: x
##
## Locations: 1
##
## Attributes:
## x
## y
## do
## zhat
## sigma2hat
Kriging_aquifer$zhat
## [1] 196.2781
Kriging_aquifer$sigma2hat
## [1] 5169.927
grid <- list(x=seq(min(aquifer$Este),max(aquifer$Este),by=20),y=seq(min(aquifer$Norte),max(aquifer$Norte),by=10))
grid$xr <- range(grid$x)
grid$xs <- grid$xr[2] - grid$xr[1]
grid$yr <- range(grid$y)
grid$ys <- grid$yr[2] - grid$yr[1]
grid$max <- max(grid$xs, grid$ys)
grid$xy <- data.frame(cbind(c(matrix(grid$x, length(grid$x), length(grid$y))),
c(matrix(grid$y, length(grid$x), length(grid$y), byrow=TRUE))))
colnames(grid$xy) <- c("x", "y")
grid$point <- point(grid$xy)
grid$krige <- krige(grid$point,aquifer_points,'resi',aquifer.vmodwave_0,maxdist=180,extrap=FALSE)
##
## Using points within 180 units of prediction points.
## Predicting..........................................................................................................................................................................................................................................
op <- par(no.readonly = TRUE)
par(pty="s")
plot(grid$xy, type="n", xlim=c(grid$xr[1], grid$xr[1]+grid$max),ylim=c(grid$yr[1], grid$yr[1]+grid$max))
image(grid$x,grid$y,matrix(grid$krige$zhat,length(grid$x),length(grid$y)),add=TRUE)
contour(grid$x,grid$y,matrix(grid$krige$zhat,length(grid$x),length(grid$y)),add=TRUE)
x11()
op <- par(no.readonly = TRUE)
par(pty="s")
plot(grid$xy, type="n", xlim=c(grid$xr[1], grid$xr[1]+grid$max),ylim=c(grid$yr[1], grid$yr[1]+grid$max))
image(grid$x,grid$y,matrix(grid$krige$sigma2hat,length(grid$x),length(grid$y)), add=TRUE)
contour(grid$x,grid$y,matrix(grid$krige$sigma2hat,length(grid$x),length(grid$y)),add=TRUE)
