Get predicted values for Lek Profile method, used iteratively in lekprofile
pred_sens(mat_in, mod_in, var_sel, step_val, grps, ysel)data.frame of only the explanatory variables used to create model
any model object with a predict method
chr string of explanatory variable to select
number of values to sequence range of selected explanatory variable
matrix of values for holding explanatory values constant, one column per variable and one row per group
chr string of response variable names for correct labelling
A list of predictions where each element is a data.frame with the predicted value of the response and the values of the explanatory variable defined by var_sel. Each element of the list corresponds to a group defined by the rows in grps at which the other explanatory variables were held constant.
Gets predicted output for a model's response variable based on matrix of explanatory variables that are restricted following Lek's profile method. The selected explanatory variable is sequenced across a range of values. All other explanatory variables are held constant at the values in grps.
lekprofile
## using nnet
library(nnet)
data(neuraldat)
set.seed(123)
mod <- nnet(Y1 ~ X1 + X2 + X3, data = neuraldat, size = 5)
#> # weights: 26
#> initial value 259.012592
#> iter 10 value 0.986480
#> iter 20 value 0.225311
#> iter 30 value 0.139585
#> iter 40 value 0.098961
#> iter 50 value 0.038200
#> iter 60 value 0.022839
#> iter 70 value 0.013774
#> iter 80 value 0.008530
#> iter 90 value 0.005172
#> iter 100 value 0.003044
#> final value 0.003044
#> stopped after 100 iterations
mat_in <- neuraldat[, c('X1', 'X2', 'X3')]
grps <- apply(mat_in, 2, quantile, seq(0, 1, by = 0.2))
pred_sens(mat_in, mod, 'X1', 100, grps, 'Y1')
#> $`1`
#> Y1 x_vars
#> 1 0.9541242 -4.075225250
#> 2 0.9509343 -3.998304986
#> 3 0.9475811 -3.921384722
#> 4 0.9440648 -3.844464458
#> 5 0.9403866 -3.767544194
#> 6 0.9365486 -3.690623931
#> 7 0.9325538 -3.613703667
#> 8 0.9284062 -3.536783403
#> 9 0.9241106 -3.459863139
#> 10 0.9196725 -3.382942876
#> 11 0.9150982 -3.306022612
#> 12 0.9103948 -3.229102348
#> 13 0.9055696 -3.152182084
#> 14 0.9006308 -3.075261820
#> 15 0.8955866 -2.998341557
#> 16 0.8904457 -2.921421293
#> 17 0.8852169 -2.844501029
#> 18 0.8799089 -2.767580765
#> 19 0.8745305 -2.690660501
#> 20 0.8690905 -2.613740238
#> 21 0.8635972 -2.536819974
#> 22 0.8580588 -2.459899710
#> 23 0.8524831 -2.382979446
#> 24 0.8468775 -2.306059183
#> 25 0.8412489 -2.229138919
#> 26 0.8356038 -2.152218655
#> 27 0.8299480 -2.075298391
#> 28 0.8242869 -1.998378127
#> 29 0.8186253 -1.921457864
#> 30 0.8129676 -1.844537600
#> 31 0.8073174 -1.767617336
#> 32 0.8016779 -1.690697072
#> 33 0.7960517 -1.613776808
#> 34 0.7904412 -1.536856545
#> 35 0.7848479 -1.459936281
#> 36 0.7792732 -1.383016017
#> 37 0.7737178 -1.306095753
#> 38 0.7681823 -1.229175490
#> 39 0.7626667 -1.152255226
#> 40 0.7571709 -1.075334962
#> 41 0.7516944 -0.998414698
#> 42 0.7462365 -0.921494434
#> 43 0.7407962 -0.844574171
#> 44 0.7353725 -0.767653907
#> 45 0.7299639 -0.690733643
#> 46 0.7245691 -0.613813379
#> 47 0.7191867 -0.536893115
#> 48 0.7138150 -0.459972852
#> 49 0.7084524 -0.383052588
#> 50 0.7030972 -0.306132324
#> 51 0.6977478 -0.229212060
#> 52 0.6924026 -0.152291797
#> 53 0.6870600 -0.075371533
#> 54 0.6817185 0.001548731
#> 55 0.6763765 0.078468995
#> 56 0.6710327 0.155389259
#> 57 0.6656858 0.232309522
#> 58 0.6603346 0.309229786
#> 59 0.6549780 0.386150050
#> 60 0.6496151 0.463070314
#> 61 0.6442450 0.539990578
#> 62 0.6388672 0.616910841
#> 63 0.6334809 0.693831105
#> 64 0.6280858 0.770751369
#> 65 0.6226817 0.847671633
#> 66 0.6172683 0.924591896
#> 67 0.6118457 1.001512160
#> 68 0.6064139 1.078432424
#> 69 0.6009733 1.155352688
#> 70 0.5955241 1.232272952
#> 71 0.5900669 1.309193215
#> 72 0.5846022 1.386113479
#> 73 0.5791308 1.463033743
#> 74 0.5736533 1.539954007
#> 75 0.5681706 1.616874271
#> 76 0.5626836 1.693794534
#> 77 0.5571932 1.770714798
#> 78 0.5517005 1.847635062
#> 79 0.5462065 1.924555326
#> 80 0.5407122 2.001475589
#> 81 0.5352186 2.078395853
#> 82 0.5297269 2.155316117
#> 83 0.5242381 2.232236381
#> 84 0.5187531 2.309156645
#> 85 0.5132730 2.386076908
#> 86 0.5077987 2.462997172
#> 87 0.5023310 2.539917436
#> 88 0.4968709 2.616837700
#> 89 0.4914190 2.693757964
#> 90 0.4859761 2.770678227
#> 91 0.4805427 2.847598491
#> 92 0.4751193 2.924518755
#> 93 0.4697064 3.001439019
#> 94 0.4643044 3.078359282
#> 95 0.4589134 3.155279546
#> 96 0.4535335 3.232199810
#> 97 0.4481649 3.309120074
#> 98 0.4428075 3.386040338
#> 99 0.4374611 3.462960601
#> 100 0.4321254 3.539880865
#>
#> $`2`
#> Y1 x_vars
#> 1 0.8031474 -4.075225250
#> 2 0.7972901 -3.998304986
#> 3 0.7914529 -3.921384722
#> 4 0.7856386 -3.844464458
#> 5 0.7798497 -3.767544194
#> 6 0.7740880 -3.690623931
#> 7 0.7683549 -3.613703667
#> 8 0.7626512 -3.536783403
#> 9 0.7569776 -3.459863139
#> 10 0.7513340 -3.382942876
#> 11 0.7457203 -3.306022612
#> 12 0.7401358 -3.229102348
#> 13 0.7345797 -3.152182084
#> 14 0.7290509 -3.075261820
#> 15 0.7235481 -2.998341557
#> 16 0.7180698 -2.921421293
#> 17 0.7126143 -2.844501029
#> 18 0.7071798 -2.767580765
#> 19 0.7017644 -2.690660501
#> 20 0.6963663 -2.613740238
#> 21 0.6909833 -2.536819974
#> 22 0.6856134 -2.459899710
#> 23 0.6802547 -2.382979446
#> 24 0.6749052 -2.306059183
#> 25 0.6695627 -2.229138919
#> 26 0.6642256 -2.152218655
#> 27 0.6588918 -2.075298391
#> 28 0.6535596 -1.998378127
#> 29 0.6482273 -1.921457864
#> 30 0.6428935 -1.844537600
#> 31 0.6375565 -1.767617336
#> 32 0.6322152 -1.690697072
#> 33 0.6268683 -1.613776808
#> 34 0.6215146 -1.536856545
#> 35 0.6161535 -1.459936281
#> 36 0.6107839 -1.383016017
#> 37 0.6054053 -1.306095753
#> 38 0.6000173 -1.229175490
#> 39 0.5946194 -1.152255226
#> 40 0.5892116 -1.075334962
#> 41 0.5837936 -0.998414698
#> 42 0.5783656 -0.921494434
#> 43 0.5729279 -0.844574171
#> 44 0.5674807 -0.767653907
#> 45 0.5620245 -0.690733643
#> 46 0.5565598 -0.613813379
#> 47 0.5510873 -0.536893115
#> 48 0.5456078 -0.459972852
#> 49 0.5401221 -0.383052588
#> 50 0.5346310 -0.306132324
#> 51 0.5291355 -0.229212060
#> 52 0.5236366 -0.152291797
#> 53 0.5181354 -0.075371533
#> 54 0.5126328 0.001548731
#> 55 0.5071299 0.078468995
#> 56 0.5016278 0.155389259
#> 57 0.4961274 0.232309522
#> 58 0.4906299 0.309229786
#> 59 0.4851361 0.386150050
#> 60 0.4796470 0.463070314
#> 61 0.4741634 0.539990578
#> 62 0.4686862 0.616910841
#> 63 0.4632160 0.693831105
#> 64 0.4577535 0.770751369
#> 65 0.4522993 0.847671633
#> 66 0.4468537 0.924591896
#> 67 0.4414172 1.001512160
#> 68 0.4359900 1.078432424
#> 69 0.4305723 1.155352688
#> 70 0.4251641 1.232272952
#> 71 0.4197654 1.309193215
#> 72 0.4143760 1.386113479
#> 73 0.4089955 1.463033743
#> 74 0.4036238 1.539954007
#> 75 0.3982601 1.616874271
#> 76 0.3929040 1.693794534
#> 77 0.3875548 1.770714798
#> 78 0.3822118 1.847635062
#> 79 0.3768739 1.924555326
#> 80 0.3715404 2.001475589
#> 81 0.3662101 2.078395853
#> 82 0.3608820 2.155316117
#> 83 0.3555549 2.232236381
#> 84 0.3502276 2.309156645
#> 85 0.3448989 2.386076908
#> 86 0.3395674 2.462997172
#> 87 0.3342319 2.539917436
#> 88 0.3288911 2.616837700
#> 89 0.3235435 2.693757964
#> 90 0.3181879 2.770678227
#> 91 0.3128229 2.847598491
#> 92 0.3074473 2.924518755
#> 93 0.3020598 3.001439019
#> 94 0.2966593 3.078359282
#> 95 0.2912447 3.155279546
#> 96 0.2858150 3.232199810
#> 97 0.2803694 3.309120074
#> 98 0.2749071 3.386040338
#> 99 0.2694274 3.462960601
#> 100 0.2639301 3.539880865
#>
#> $`3`
#> Y1 x_vars
#> 1 0.7692307 -4.075225250
#> 2 0.7634822 -3.998304986
#> 3 0.7577655 -3.921384722
#> 4 0.7520810 -3.844464458
#> 5 0.7464286 -3.767544194
#> 6 0.7408078 -3.690623931
#> 7 0.7352180 -3.613703667
#> 8 0.7296580 -3.536783403
#> 9 0.7241268 -3.459863139
#> 10 0.7186227 -3.382942876
#> 11 0.7131443 -3.306022612
#> 12 0.7076896 -3.229102348
#> 13 0.7022569 -3.152182084
#> 14 0.6968441 -3.075261820
#> 15 0.6914493 -2.998341557
#> 16 0.6860702 -2.921421293
#> 17 0.6807049 -2.844501029
#> 18 0.6753512 -2.767580765
#> 19 0.6700071 -2.690660501
#> 20 0.6646705 -2.613740238
#> 21 0.6593395 -2.536819974
#> 22 0.6540122 -2.459899710
#> 23 0.6486867 -2.382979446
#> 24 0.6433613 -2.306059183
#> 25 0.6380344 -2.229138919
#> 26 0.6327045 -2.152218655
#> 27 0.6273703 -2.075298391
#> 28 0.6220305 -1.998378127
#> 29 0.6166840 -1.921457864
#> 30 0.6113299 -1.844537600
#> 31 0.6059673 -1.767617336
#> 32 0.6005957 -1.690697072
#> 33 0.5952143 -1.613776808
#> 34 0.5898230 -1.536856545
#> 35 0.5844215 -1.459936281
#> 36 0.5790096 -1.383016017
#> 37 0.5735875 -1.306095753
#> 38 0.5681553 -1.229175490
#> 39 0.5627134 -1.152255226
#> 40 0.5572621 -1.075334962
#> 41 0.5518020 -0.998414698
#> 42 0.5463337 -0.921494434
#> 43 0.5408579 -0.844574171
#> 44 0.5353756 -0.767653907
#> 45 0.5298874 -0.690733643
#> 46 0.5243944 -0.613813379
#> 47 0.5188976 -0.536893115
#> 48 0.5133979 -0.459972852
#> 49 0.5078964 -0.383052588
#> 50 0.5023942 -0.306132324
#> 51 0.4968922 -0.229212060
#> 52 0.4913914 -0.152291797
#> 53 0.4858930 -0.075371533
#> 54 0.4803978 0.001548731
#> 55 0.4749068 0.078468995
#> 56 0.4694208 0.155389259
#> 57 0.4639407 0.232309522
#> 58 0.4584670 0.309229786
#> 59 0.4530005 0.386150050
#> 60 0.4475418 0.463070314
#> 61 0.4420912 0.539990578
#> 62 0.4366491 0.616910841
#> 63 0.4312158 0.693831105
#> 64 0.4257914 0.770751369
#> 65 0.4203759 0.847671633
#> 66 0.4149694 0.924591896
#> 67 0.4095715 1.001512160
#> 68 0.4041821 1.078432424
#> 69 0.3988008 1.155352688
#> 70 0.3934269 1.232272952
#> 71 0.3880600 1.309193215
#> 72 0.3826994 1.386113479
#> 73 0.3773442 1.463033743
#> 74 0.3719936 1.539954007
#> 75 0.3666466 1.616874271
#> 76 0.3613022 1.693794534
#> 77 0.3559594 1.770714798
#> 78 0.3506168 1.847635062
#> 79 0.3452734 1.924555326
#> 80 0.3399279 2.001475589
#> 81 0.3345790 2.078395853
#> 82 0.3292253 2.155316117
#> 83 0.3238656 2.232236381
#> 84 0.3184986 2.309156645
#> 85 0.3131230 2.386076908
#> 86 0.3077375 2.462997172
#> 87 0.3023408 2.539917436
#> 88 0.2969319 2.616837700
#> 89 0.2915096 2.693757964
#> 90 0.2860729 2.770678227
#> 91 0.2806210 2.847598491
#> 92 0.2751531 2.924518755
#> 93 0.2696685 3.001439019
#> 94 0.2641669 3.078359282
#> 95 0.2586480 3.155279546
#> 96 0.2531116 3.232199810
#> 97 0.2475581 3.309120074
#> 98 0.2419878 3.386040338
#> 99 0.2364015 3.462960601
#> 100 0.2308001 3.539880865
#>
#> $`4`
#> Y1 x_vars
#> 1 0.7416348 -4.075225250
#> 2 0.7360134 -3.998304986
#> 3 0.7304242 -3.921384722
#> 4 0.7248659 -3.844464458
#> 5 0.7193373 -3.767544194
#> 6 0.7138367 -3.690623931
#> 7 0.7083624 -3.613703667
#> 8 0.7029125 -3.536783403
#> 9 0.6974851 -3.459863139
#> 10 0.6920780 -3.382942876
#> 11 0.6866891 -3.306022612
#> 12 0.6813164 -3.229102348
#> 13 0.6759576 -3.152182084
#> 14 0.6706106 -3.075261820
#> 15 0.6652733 -2.998341557
#> 16 0.6599435 -2.921421293
#> 17 0.6546194 -2.844501029
#> 18 0.6492989 -2.767580765
#> 19 0.6439802 -2.690660501
#> 20 0.6386616 -2.613740238
#> 21 0.6333414 -2.536819974
#> 22 0.6280182 -2.459899710
#> 23 0.6226904 -2.382979446
#> 24 0.6173570 -2.306059183
#> 25 0.6120167 -2.229138919
#> 26 0.6066687 -2.152218655
#> 27 0.6013120 -2.075298391
#> 28 0.5959460 -1.998378127
#> 29 0.5905702 -1.921457864
#> 30 0.5851842 -1.844537600
#> 31 0.5797877 -1.767617336
#> 32 0.5743807 -1.690697072
#> 33 0.5689633 -1.613776808
#> 34 0.5635355 -1.536856545
#> 35 0.5580977 -1.459936281
#> 36 0.5526503 -1.383016017
#> 37 0.5471938 -1.306095753
#> 38 0.5417289 -1.229175490
#> 39 0.5362563 -1.152255226
#> 40 0.5307767 -1.075334962
#> 41 0.5252911 -0.998414698
#> 42 0.5198004 -0.921494434
#> 43 0.5143055 -0.844574171
#> 44 0.5088074 -0.767653907
#> 45 0.5033072 -0.690733643
#> 46 0.4978059 -0.613813379
#> 47 0.4923045 -0.536893115
#> 48 0.4868040 -0.459972852
#> 49 0.4813055 -0.383052588
#> 50 0.4758099 -0.306132324
#> 51 0.4703180 -0.229212060
#> 52 0.4648307 -0.152291797
#> 53 0.4593489 -0.075371533
#> 54 0.4538732 0.001548731
#> 55 0.4484042 0.078468995
#> 56 0.4429424 0.155389259
#> 57 0.4374884 0.232309522
#> 58 0.4320424 0.309229786
#> 59 0.4266046 0.386150050
#> 60 0.4211753 0.463070314
#> 61 0.4157544 0.539990578
#> 62 0.4103418 0.616910841
#> 63 0.4049373 0.693831105
#> 64 0.3995407 0.770751369
#> 65 0.3941515 0.847671633
#> 66 0.3887692 0.924591896
#> 67 0.3833932 1.001512160
#> 68 0.3780228 1.078432424
#> 69 0.3726571 1.155352688
#> 70 0.3672953 1.232272952
#> 71 0.3619364 1.309193215
#> 72 0.3565794 1.386113479
#> 73 0.3512231 1.463033743
#> 74 0.3458664 1.539954007
#> 75 0.3405081 1.616874271
#> 76 0.3351469 1.693794534
#> 77 0.3297816 1.770714798
#> 78 0.3244108 1.847635062
#> 79 0.3190334 1.924555326
#> 80 0.3136479 2.001475589
#> 81 0.3082531 2.078395853
#> 82 0.3028479 2.155316117
#> 83 0.2974310 2.232236381
#> 84 0.2920014 2.309156645
#> 85 0.2865581 2.386076908
#> 86 0.2811002 2.462997172
#> 87 0.2756268 2.539917436
#> 88 0.2701374 2.616837700
#> 89 0.2646315 2.693757964
#> 90 0.2591088 2.770678227
#> 91 0.2535692 2.847598491
#> 92 0.2480129 2.924518755
#> 93 0.2424403 3.001439019
#> 94 0.2368520 3.078359282
#> 95 0.2312490 3.155279546
#> 96 0.2256325 3.232199810
#> 97 0.2200041 3.309120074
#> 98 0.2143658 3.386040338
#> 99 0.2087198 3.462960601
#> 100 0.2030689 3.539880865
#>
#> $`5`
#> Y1 x_vars
#> 1 0.7134240 -4.075225250
#> 2 0.7079330 -3.998304986
#> 3 0.7024687 -3.921384722
#> 4 0.6970290 -3.844464458
#> 5 0.6916119 -3.767544194
#> 6 0.6862152 -3.690623931
#> 7 0.6808368 -3.613703667
#> 8 0.6754743 -3.536783403
#> 9 0.6701256 -3.459863139
#> 10 0.6647886 -3.382942876
#> 11 0.6594609 -3.306022612
#> 12 0.6541406 -3.229102348
#> 13 0.6488255 -3.152182084
#> 14 0.6435138 -3.075261820
#> 15 0.6382035 -2.998341557
#> 16 0.6328930 -2.921421293
#> 17 0.6275805 -2.844501029
#> 18 0.6222646 -2.767580765
#> 19 0.6169439 -2.690660501
#> 20 0.6116172 -2.613740238
#> 21 0.6062832 -2.536819974
#> 22 0.6009412 -2.459899710
#> 23 0.5955902 -2.382979446
#> 24 0.5902296 -2.306059183
#> 25 0.5848589 -2.229138919
#> 26 0.5794777 -2.152218655
#> 27 0.5740858 -2.075298391
#> 28 0.5686831 -1.998378127
#> 29 0.5632697 -1.921457864
#> 30 0.5578457 -1.844537600
#> 31 0.5524114 -1.767617336
#> 32 0.5469674 -1.690697072
#> 33 0.5415141 -1.613776808
#> 34 0.5360521 -1.536856545
#> 35 0.5305821 -1.459936281
#> 36 0.5251051 -1.383016017
#> 37 0.5196218 -1.306095753
#> 38 0.5141331 -1.229175490
#> 39 0.5086401 -1.152255226
#> 40 0.5031436 -1.075334962
#> 41 0.4976449 -0.998414698
#> 42 0.4921447 -0.921494434
#> 43 0.4866442 -0.844574171
#> 44 0.4811445 -0.767653907
#> 45 0.4756463 -0.690733643
#> 46 0.4701507 -0.613813379
#> 47 0.4646586 -0.536893115
#> 48 0.4591707 -0.459972852
#> 49 0.4536879 -0.383052588
#> 50 0.4482107 -0.306132324
#> 51 0.4427399 -0.229212060
#> 52 0.4372759 -0.152291797
#> 53 0.4318190 -0.075371533
#> 54 0.4263697 0.001548731
#> 55 0.4209281 0.078468995
#> 56 0.4154942 0.155389259
#> 57 0.4100682 0.232309522
#> 58 0.4046498 0.309229786
#> 59 0.3992388 0.386150050
#> 60 0.3938350 0.463070314
#> 61 0.3884377 0.539990578
#> 62 0.3830465 0.616910841
#> 63 0.3776608 0.693831105
#> 64 0.3722797 0.770751369
#> 65 0.3669025 0.847671633
#> 66 0.3615282 0.924591896
#> 67 0.3561559 1.001512160
#> 68 0.3507844 1.078432424
#> 69 0.3454127 1.155352688
#> 70 0.3400396 1.232272952
#> 71 0.3346638 1.309193215
#> 72 0.3292842 1.386113479
#> 73 0.3238994 1.463033743
#> 74 0.3185083 1.539954007
#> 75 0.3131095 1.616874271
#> 76 0.3077018 1.693794534
#> 77 0.3022840 1.770714798
#> 78 0.2968551 1.847635062
#> 79 0.2914138 1.924555326
#> 80 0.2859593 2.001475589
#> 81 0.2804905 2.078395853
#> 82 0.2750069 2.155316117
#> 83 0.2695077 2.232236381
#> 84 0.2639926 2.309156645
#> 85 0.2584611 2.386076908
#> 86 0.2529134 2.462997172
#> 87 0.2473494 2.539917436
#> 88 0.2417697 2.616837700
#> 89 0.2361750 2.693757964
#> 90 0.2305661 2.770678227
#> 91 0.2249444 2.847598491
#> 92 0.2193114 2.924518755
#> 93 0.2136692 3.001439019
#> 94 0.2080201 3.078359282
#> 95 0.2023666 3.155279546
#> 96 0.1967120 3.232199810
#> 97 0.1910598 3.309120074
#> 98 0.1854136 3.386040338
#> 99 0.1797780 3.462960601
#> 100 0.1741574 3.539880865
#>
#> $`6`
#> Y1 x_vars
#> 1 0.58556438 -4.075225250
#> 2 0.58026773 -3.998304986
#> 3 0.57496104 -3.921384722
#> 4 0.56964354 -3.844464458
#> 5 0.56431465 -3.767544194
#> 6 0.55897390 -3.690623931
#> 7 0.55362099 -3.613703667
#> 8 0.54825576 -3.536783403
#> 9 0.54287817 -3.459863139
#> 10 0.53748833 -3.382942876
#> 11 0.53208646 -3.306022612
#> 12 0.52667291 -3.229102348
#> 13 0.52124814 -3.152182084
#> 14 0.51581271 -3.075261820
#> 15 0.51036724 -2.998341557
#> 16 0.50491248 -2.921421293
#> 17 0.49944921 -2.844501029
#> 18 0.49397828 -2.767580765
#> 19 0.48850059 -2.690660501
#> 20 0.48301707 -2.613740238
#> 21 0.47752867 -2.536819974
#> 22 0.47203635 -2.459899710
#> 23 0.46654106 -2.382979446
#> 24 0.46104375 -2.306059183
#> 25 0.45554531 -2.229138919
#> 26 0.45004664 -2.152218655
#> 27 0.44454856 -2.075298391
#> 28 0.43905182 -1.998378127
#> 29 0.43355714 -1.921457864
#> 30 0.42806513 -1.844537600
#> 31 0.42257633 -1.767617336
#> 32 0.41709119 -1.690697072
#> 33 0.41161007 -1.613776808
#> 34 0.40613321 -1.536856545
#> 35 0.40066075 -1.459936281
#> 36 0.39519276 -1.383016017
#> 37 0.38972915 -1.306095753
#> 38 0.38426975 -1.229175490
#> 39 0.37881429 -1.152255226
#> 40 0.37336238 -1.075334962
#> 41 0.36791353 -0.998414698
#> 42 0.36246717 -0.921494434
#> 43 0.35702262 -0.844574171
#> 44 0.35157911 -0.767653907
#> 45 0.34613583 -0.690733643
#> 46 0.34069185 -0.613813379
#> 47 0.33524622 -0.536893115
#> 48 0.32979792 -0.459972852
#> 49 0.32434590 -0.383052588
#> 50 0.31888909 -0.306132324
#> 51 0.31342640 -0.229212060
#> 52 0.30795675 -0.152291797
#> 53 0.30247907 -0.075371533
#> 54 0.29699234 0.001548731
#> 55 0.29149557 0.078468995
#> 56 0.28598786 0.155389259
#> 57 0.28046839 0.232309522
#> 58 0.27493646 0.309229786
#> 59 0.26939148 0.386150050
#> 60 0.26383303 0.463070314
#> 61 0.25826084 0.539990578
#> 62 0.25267487 0.616910841
#> 63 0.24707527 0.693831105
#> 64 0.24146243 0.770751369
#> 65 0.23583701 0.847671633
#> 66 0.23019994 0.924591896
#> 67 0.22455248 1.001512160
#> 68 0.21889618 1.078432424
#> 69 0.21323296 1.155352688
#> 70 0.20756508 1.232272952
#> 71 0.20189519 1.309193215
#> 72 0.19622630 1.386113479
#> 73 0.19056183 1.463033743
#> 74 0.18490560 1.539954007
#> 75 0.17926180 1.616874271
#> 76 0.17363504 1.693794534
#> 77 0.16803030 1.770714798
#> 78 0.16245293 1.847635062
#> 79 0.15690861 1.924555326
#> 80 0.15140336 2.001475589
#> 81 0.14594346 2.078395853
#> 82 0.14053546 2.155316117
#> 83 0.13518610 2.232236381
#> 84 0.12990225 2.309156645
#> 85 0.12469089 2.386076908
#> 86 0.11955903 2.462997172
#> 87 0.11451363 2.539917436
#> 88 0.10956156 2.616837700
#> 89 0.10470953 2.693757964
#> 90 0.09996398 2.770678227
#> 91 0.09533106 2.847598491
#> 92 0.09081654 2.924518755
#> 93 0.08642577 3.001439019
#> 94 0.08216358 3.078359282
#> 95 0.07803426 3.155279546
#> 96 0.07404154 3.232199810
#> 97 0.07018849 3.309120074
#> 98 0.06647755 3.386040338
#> 99 0.06291050 3.462960601
#> 100 0.05948844 3.539880865
#>