Nothing
tests/testthat/_snaps/estimate_model.md
In proximetricsR: Spectral Preprocessing and Chemometric Calibration of NIR Sensors
Modified partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 5
$method$type
[1] "modified"
$intercept
[1] 0.255678
$x_means
1001 1061 1121 1181 1241 1301 1361 1421
0.156301 0.141979 0.132416 0.154116 0.139626 0.128845 0.154316 0.243516
1481 1541 1601 1661
0.283892 0.269643 0.259751 0.256310
$projection_m
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.386056 0.376287 0.373894 0.465212 0.430333 0.432307 0.467938
ncomp_2 -0.221344 -0.290215 -0.336661 -0.207807 -0.325815 -0.413097 -0.486687
ncomp_3 0.305650 0.313763 -0.318586 0.438165 -0.125121 -0.541374 -0.541512
ncomp_4 -0.212852 -0.167362 -0.266566 0.477972 0.300118 0.096730 0.102746
ncomp_5 -0.143109 0.169607 0.115804 0.241869 -0.127278 -0.176347 -0.176138
1421 1481 1541 1601 1661
ncomp_1 0.587879 0.618185 0.621539 0.611514 0.567892
ncomp_2 0.583240 0.589496 0.581114 0.548176 0.371549
ncomp_3 0.444650 0.298386 0.580720 -0.026668 -0.785578
ncomp_4 -0.313264 0.106308 0.254067 0.198561 -0.541332
ncomp_5 -0.115708 -0.086607 -0.053844 0.208091 0.083054
$coefficients
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.103782 0.101155 0.100512 0.125061 0.115685 0.116215 0.125794
ncomp_2 -0.144160 -0.223933 -0.276604 -0.107718 -0.249282 -0.346522 -0.419376
ncomp_3 4.501119 4.544642 -5.118488 6.551527 -2.150876 -8.574340 -8.649288
ncomp_4 1.456464 2.150675 -8.931479 13.388482 2.142037 -7.190704 -7.179602
ncomp_5 -4.187651 8.839861 -4.364233 22.927640 -2.877720 -14.145698 -14.126364
1421 1481 1541 1601 1661
ncomp_1 0.158037 0.166184 0.167085 0.164391 0.152664
ncomp_2 0.811361 0.826517 0.818029 0.778438 0.568860
ncomp_3 7.569162 5.361394 9.643821 0.373143 -11.370375
ncomp_4 3.088199 6.882036 13.278020 3.213374 -19.113641
ncomp_5 -1.475245 3.466301 11.154465 11.420359 -15.838032
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.001674 1.5e-05 6.0e-06 5e-06 0
2 0.000067 7.2e-05 2.4e-05 0e+00 0
3 0.003582 3.6e-05 5.0e-06 0e+00 0
4 0.002193 2.4e-05 2.3e-05 0e+00 0
5 0.000950 6.4e-05 1.1e-05 4e-06 0
6 0.001454 6.3e-05 3.5e-05 0e+00 0
$weights
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.386056 0.376287 0.373894 0.465212 0.430333 0.432307 0.467938
ncomp_2 -0.305944 -0.372674 -0.418596 -0.309753 -0.420117 -0.507832 -0.589230
ncomp_3 0.344863 0.348386 -0.286516 0.488263 -0.085231 -0.505444 -0.504531
ncomp_4 -0.318826 -0.287908 -0.218463 0.340892 0.298581 0.196606 0.191611
ncomp_5 -0.155027 0.155027 0.155027 0.155027 -0.155027 -0.155027 -0.155027
1421 1481 1541 1601 1661
ncomp_1 0.587879 0.618185 0.621539 0.611514 0.567892
ncomp_2 0.454413 0.454028 0.444911 0.414170 0.247102
ncomp_3 0.548811 0.406767 0.689129 0.078855 -0.694225
ncomp_4 -0.310361 0.152552 0.220102 0.328246 -0.231915
ncomp_5 -0.155027 -0.155027 -0.155027 0.155027 0.155027
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.175124 -0.052980 -0.002623 0.000554 0.000977
2 0.044461 0.006160 0.011080 0.003636 -0.000125
3 -0.349461 0.072248 -0.005045 0.001648 0.000264
4 0.381650 0.060541 0.000179 -0.003554 -0.000136
5 0.091422 -0.042239 -0.007126 0.002046 -0.000823
6 -0.343196 -0.043731 0.003535 -0.004331 -0.000157
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.292084 0.055545 0.006609 0.003219 0.000593
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.599565 -0.953819 -0.396936 0.172177 1.646273
2 0.152221 0.110907 1.676498 1.129560 -0.211287
3 -1.196438 1.300713 -0.763316 0.512031 0.445556
4 1.306643 1.089938 0.027082 -1.103807 -0.228606
5 0.312999 -0.760437 -1.078140 0.635439 -1.387179
6 -1.174990 -0.787302 0.534812 -1.345400 -0.264756
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.268825 1.120165 15.198028 14.304093 39.439320
$x_loadings
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.188171 0.191643 0.189747 0.196015 0.181856 0.172154 0.161319
ncomp_2 -0.342646 -0.332390 -0.307079 -0.160167 -0.183955 -0.143261 -0.065515
ncomp_3 0.636215 0.236118 -0.006184 0.062703 -0.116423 -0.227503 -0.233810
ncomp_4 -0.962673 -0.375127 -0.111364 0.450249 0.399319 0.208065 0.215325
ncomp_5 -0.518083 0.205320 0.261137 1.517559 -0.086519 -0.599734 -0.647469
1421 1481 1541 1601 1661
ncomp_1 0.156664 0.148181 0.146546 0.151717 0.171470
ncomp_2 0.137285 0.202995 0.217735 0.220092 0.250606
ncomp_3 0.088125 0.075157 0.077565 -0.017979 -0.420755
ncomp_4 -0.053937 0.282731 0.080441 0.073131 -0.449658
ncomp_5 -0.010474 -1.138156 -0.185400 0.374263 0.906366
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.302756 0.243410 0.203539 0.211468 0.25000
2 0.267631 0.274531 0.442929 0.494945 0.49000
3 0.161734 0.242665 0.165992 0.189571 0.20000
4 0.358276 0.426091 0.428811 0.377981 0.37263
5 0.280255 0.232941 0.124646 0.153908 0.12144
6 0.163419 0.114433 0.168153 0.106197 0.10000
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.128954 0.222369
ncomp_2 2 0.112951 0.215469
ncomp_3 3 0.051657 0.068153
ncomp_4 4 0.023406 0.038532
ncomp_5 5 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.10000 0.12144 0.22500 0.37263 0.49000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
pls_var 0.030345 0.001929 0.000034 0.000019 2.0e-06
x_expl_var 0.938630 0.059665 0.001056 0.000586 6.3e-05
x_expl_var_cum 0.938630 0.998295 0.999351 0.999937 1.0e+00
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
y_explained_variance 0.270475 0.44031 0.882935 0.975967 1
Standard partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 4
$method$type
[1] "standard"
$intercept
[1] 12.05516
$x_means
1004 1064 1124 1184 1244 1304 1364 1424
0.221025 0.206133 0.196139 0.218410 0.199299 0.186575 0.211677 0.305766
1484 1544 1604 1664
0.338529 0.322845 0.316359 0.319857
$projection_m
1004 1064 1124 1184 1244 1304 1364
ncomp_1 -0.352506 -0.352012 -0.342202 -0.319507 -0.308179 -0.292365 -0.268522
ncomp_2 -0.208437 -0.297937 -0.317715 -0.131081 -0.134116 -0.138987 -0.046493
ncomp_3 -0.094642 -0.118608 -0.103898 0.005833 0.166656 0.090884 0.097811
ncomp_4 0.686131 -0.026768 -0.319786 -0.520137 0.043020 -0.004351 0.166010
1424 1484 1544 1604 1664
ncomp_1 -0.222842 -0.214231 -0.225276 -0.245329 -0.271285
ncomp_2 0.568720 0.474654 0.309223 0.223243 0.131239
ncomp_3 0.773159 0.305979 -0.067272 -0.296723 -0.595707
ncomp_4 0.360298 0.149876 0.026407 0.031964 -0.545586
$coefficients
1004 1064 1124 1184 1244 1304
ncomp_1 -4.909466 -4.902584 -4.76596 -4.449889 -4.292108 -4.071867
ncomp_2 -14.049616 -17.967426 -18.69806 -10.197931 -10.173213 -10.166574
ncomp_3 -78.991197 -99.353351 -89.99024 -6.195663 104.182650 52.196261
ncomp_4 958.658631 -139.835718 -573.60915 -792.810271 169.242025 45.615704
1364 1424 1484 1544 1604 1664
ncomp_1 -3.739793 -3.103599 -2.983672 -3.137501 -3.416783 -3.778283
ncomp_2 -5.778568 21.835314 17.830370 10.422225 6.372639 1.976669
ncomp_3 61.336980 552.359901 227.786244 -35.738321 -197.232362 -406.784398
ncomp_4 312.397436 1097.246636 454.446557 4.198222 -148.891955 -1231.885826
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.000073 0.000008 0.0e+00 0e+00
2 0.000189 0.000164 1.3e-05 0e+00
3 0.000025 0.000014 6.0e-06 6e-06
4 0.000288 0.000031 2.9e-05 0e+00
5 0.004131 0.000006 1.0e-06 1e-06
6 0.002893 0.000056 2.0e-06 1e-06
$weights
1004 1064 1124 1184 1244 1304 1364
ncomp_1 -0.352506 -0.352012 -0.342202 -0.319507 -0.308179 -0.292365 -0.268522
ncomp_2 -0.196115 -0.285633 -0.305753 -0.119913 -0.123343 -0.128767 -0.037107
ncomp_3 0.002683 0.020508 0.044453 0.067039 0.229279 0.155782 0.119520
ncomp_4 0.735042 0.034528 -0.266091 -0.523152 -0.043109 -0.051321 0.115461
1424 1484 1544 1604 1664
ncomp_1 -0.222842 -0.214231 -0.225276 -0.245329 -0.271285
ncomp_2 0.576509 0.482142 0.317097 0.231818 0.140722
ncomp_3 0.507607 0.084348 -0.211658 -0.400962 -0.656987
ncomp_4 -0.039272 -0.008255 0.061174 0.185312 -0.237723
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -0.652409 -0.008325 -0.002518 0.000000
2 0.017218 0.009497 0.009570 -0.003512
3 0.168564 -0.004393 -0.002978 -0.001101
4 0.064331 0.016437 0.004680 0.005253
5 0.232242 -0.058922 -0.001895 0.000273
6 0.170055 0.045707 -0.006859 -0.000913
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
0.329042 0.034670 0.005989 0.002900
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -1.982757 -0.240119 -0.420422 0.000014
2 0.052327 0.273932 1.597916 -1.211047
3 0.512288 -0.126721 -0.497208 -0.379815
4 0.195509 0.474091 0.781498 1.811392
5 0.705813 -1.699537 -0.316436 0.094236
6 0.516821 1.318354 -1.145348 -0.314779
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4
13.92734 43.85098 686.17779 1512.32130
$x_loadings
1004 1064 1124 1184 1244 1304 1364
ncomp_1 -0.345650 -0.342027 -0.331514 -0.315316 -0.303867 -0.287864 -0.267225
ncomp_2 -0.197368 -0.295209 -0.326510 -0.151215 -0.230401 -0.201506 -0.092915
ncomp_3 -0.377189 0.002664 0.181970 0.337405 0.251558 0.182304 0.059849
ncomp_4 0.704817 0.051731 -0.240292 -0.505120 -0.021775 -0.071157 0.081431
1424 1484 1544 1604 1664
ncomp_1 -0.242994 -0.231085 -0.236361 -0.253432 -0.276204
ncomp_2 0.339492 0.442758 0.415927 0.419040 0.447489
ncomp_3 0.527903 0.088615 -0.243272 -0.496732 -0.534131
ncomp_4 -0.107514 0.039901 0.145769 0.236409 -0.342154
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 2.968836 2.603784 0.876079 0.87614
2 12.294958 12.711417 19.277984 13.96655
3 14.402809 14.210155 12.166901 10.50110
4 12.951117 13.671878 16.883407 24.82784
5 15.289670 12.705862 11.405482 11.81878
6 14.423582 16.427876 11.721119 10.34056
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 6.445988 11.684936
ncomp_2 2 6.264140 10.964174
ncomp_3 3 4.727772 7.752645
ncomp_4 4 1.765347 3.301101
$y_quantiles
0% 25% 50% 75% 100%
0.93000 7.20000 12.56746 14.43000 24.63605
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
pls_var 0.108401 0.001464 0.000045 0.000009
x_expl_var 0.986173 0.013319 0.000413 0.000079
x_expl_var_cum 0.986173 0.999493 0.999906 0.999985
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
y_explained_variance 0.335737 0.372687 0.642666 0.950178
NIRWise PLUS partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 5
$method$type
[1] "nwp"
$intercept
[1] 0.645529
$x_means
1007 1067 1127 1187 1247 1307 1367 1427
0.203432 0.187614 0.176879 0.198057 0.176160 0.163493 0.191022 0.280387
1487 1547 1607 1667
0.307658 0.290943 0.282915 0.287492
$projection_m
1007 1067 1127 1187 1247 1307
ncomp_1 -0.771415 -0.803827 -0.821552 -0.762773 -0.825493 -0.833042
ncomp_2 0.408081 -1.540140 -2.380717 1.056392 -3.136545 -3.361961
ncomp_3 11.359377 7.538915 1.841580 13.792588 -15.389603 -13.788223
ncomp_4 -18.103238 -16.391062 18.407872 17.245724 -8.436534 19.138751
ncomp_5 -1.321629 -1.113247 -1.049927 2.905569 -2.168114 2.151139
1367 1427 1487 1547 1607 1667
ncomp_1 -0.807784 -0.711102 -0.666442 -0.661056 -0.663381 -0.678925
ncomp_2 -3.485638 2.612674 2.813504 3.069369 2.910322 3.888454
ncomp_3 -15.092057 -7.832673 -6.343380 0.055951 -2.188173 16.097858
ncomp_4 -15.388645 -58.979379 -54.969402 39.178013 10.689167 65.571415
ncomp_5 1.854712 0.641378 0.710483 1.704556 -2.574289 -1.243071
$coefficients
1007 1067 1127 1187 1247 1307
ncomp_1 -0.771415 -0.803827 -0.821552 -0.762773 -0.825493 -0.833042
ncomp_2 -0.363335 -2.343967 -3.202269 0.293619 -3.962038 -4.195004
ncomp_3 10.996042 5.194948 -1.360688 14.086207 -19.351641 -17.983227
ncomp_4 -7.107196 -11.196114 17.047184 31.331931 -27.788175 1.155525
ncomp_5 -8.428825 -12.309360 15.997257 34.237500 -29.956289 3.306663
1367 1427 1487 1547 1607 1667
ncomp_1 -0.807784 -0.711102 -0.666442 -0.661056 -0.663381 -0.678925
ncomp_2 -4.293422 1.901572 2.147062 2.408313 2.246941 3.209529
ncomp_3 -19.385479 -5.931101 -4.196318 2.464264 0.058768 19.307387
ncomp_4 -34.774124 -64.910480 -59.165720 41.642278 10.747935 84.878803
ncomp_5 -32.919412 -64.269102 -58.455237 43.346834 8.173646 83.635732
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.000282 0.000019 1.1e-05 1e-05 0
2 0.000160 0.000143 4.0e-06 4e-06 0
3 0.000075 0.000053 1.2e-05 2e-06 0
4 0.001254 0.000111 1.0e-06 0e+00 0
5 0.001158 0.000009 6.0e-06 1e-06 0
6 0.000233 0.000020 1.0e-06 1e-06 0
$weights
1007 1067 1127 1187 1247 1307
ncomp_1 -0.771415 -0.803827 -0.821552 -0.762773 -0.825493 -0.833042
ncomp_2 -0.179670 -2.152586 -3.006667 0.475225 -3.765499 -3.996667
ncomp_3 9.002929 9.120367 5.114709 10.121504 -10.571743 -8.522210
ncomp_4 -36.102434 -28.524871 15.848990 -4.720158 18.632644 43.343044
ncomp_5 -1.988343 -1.988343 -1.988343 1.988343 -1.988343 1.988343
1367 1427 1487 1547 1607 1667
ncomp_1 -0.807784 -0.711102 -0.666442 -0.661056 -0.663381 -0.678925
ncomp_2 -4.101099 2.070876 2.305734 2.565702 2.404883 3.371173
ncomp_3 -9.522297 -14.598702 -13.434023 -7.549642 -9.471656 6.774679
ncomp_4 10.976964 -42.796820 -41.379160 41.746290 17.093636 40.650018
ncomp_5 1.988343 1.988343 1.988343 1.988343 -1.988343 -1.988343
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 -0.293017 -0.119415 0.108964 0.083420 -0.015482
2 -0.340266 0.100386 0.303067 -0.058447 0.009731
3 0.033201 -0.069739 -0.145714 0.328965 0.007758
4 -0.226583 0.237061 -0.298024 -0.118167 -0.002410
5 0.137690 -0.285454 -0.091637 -0.234544 0.004185
6 0.688975 0.137162 0.123343 -0.001228 -0.003781
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.386711 0.192715 0.217892 0.193685 0.009297
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 -0.757716 -0.619643 0.500084 0.430702 -1.665229
2 -0.879898 0.520901 1.390906 -0.301762 1.046627
3 0.085854 -0.361877 -0.668743 1.698456 0.834489
4 -0.585922 1.230110 -1.367759 -0.610098 -0.259243
5 0.356054 -1.481222 -0.420563 -1.210960 0.450085
6 1.781627 0.711731 0.566075 -0.006338 -0.406729
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1.044348 8.370523 26.564290 116.537933 111.488775
$x_loadings
1007 1067 1127 1187 1247 1307 1367
ncomp_1 -0.137043 -0.135264 -0.130153 -0.134465 -0.117562 -0.106943 -0.101084
ncomp_2 -0.024532 -0.035390 -0.038883 -0.019936 -0.027786 -0.024830 -0.012436
ncomp_3 0.021183 0.008959 0.000247 0.020023 -0.005650 -0.011475 -0.005068
ncomp_4 -0.004362 -0.001620 0.000815 -0.001236 0.000331 0.003061 0.000441
ncomp_5 -0.066891 -0.042576 -0.037801 0.162538 -0.012846 0.002107 0.043478
1427 1487 1547 1607 1667
ncomp_1 -0.094558 -0.087373 -0.084663 -0.088106 -0.100729
ncomp_2 0.036112 0.049101 0.046169 0.049066 0.039353
ncomp_3 -0.005734 -0.007359 -0.007781 -0.008835 -0.001053
ncomp_4 -0.004056 -0.002539 0.002750 0.001336 0.005352
ncomp_5 0.009474 0.013766 0.019029 -0.057118 -0.035307
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.352512 0.233097 0.342062 0.425482 0.410000
2 0.305263 0.405648 0.708716 0.650269 0.660000
3 0.678730 0.608991 0.463277 0.792242 0.800000
4 0.418947 0.656008 0.357984 0.239817 0.237407
5 0.783219 0.497765 0.406127 0.171583 0.175768
6 1.334504 1.471666 1.595009 1.593781 1.590000
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.349595 0.607452
ncomp_2 2 0.291680 0.418601
ncomp_3 3 0.193908 0.336723
ncomp_4 4 0.009297 0.015482
ncomp_5 5 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.175768 0.237407 0.535000 0.800000 1.590000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
pls_var 0.022316 0.000561 0.000064 0.000004 0.000004
x_expl_var 0.972452 0.024453 0.002785 0.000154 0.000156
x_expl_var_cum 0.972452 0.996905 0.999690 0.999844 1.000000
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
y_explained_variance 0.550281 0.686942 0.861643 0.999682 1
Modified extended partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 3
$method$type
[1] "modified"
$method$min_w
[1] 5
$method$max_w
[1] 10
$intercept
[1] 0.449116
$x_means
1010 1070 1130 1190 1250 1310 1370 1430
0.186961 0.171753 0.162385 0.182015 0.161207 0.150650 0.181972 0.279759
1490 1550 1610 1670
0.303068 0.284918 0.275373 0.281642
$projection_m
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.116575 0.454952 0.594281 0.822096 0.330613 0.040072 -0.078270
ncomp_2 -3.418721 -1.408624 1.011876 5.065428 1.199299 -0.072803 0.439909
ncomp_3 -0.791997 -0.209842 0.450545 0.008957 0.404531 0.345416 0.649225
1430 1490 1550 1610 1670
ncomp_1 -0.316946 -0.679929 -0.770104 -0.615597 0.102257
ncomp_2 -0.239535 -2.839009 -2.826251 -0.417049 3.505480
ncomp_3 0.126864 -0.709911 0.228005 0.269405 -0.771200
$coefficients
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.219049 0.854873 1.116678 1.544751 0.621235 0.075298 -0.147072
ncomp_2 -23.638862 -8.975362 8.178167 36.894390 8.990673 -0.432765 2.922878
ncomp_3 -34.727129 -11.913234 14.485976 37.019795 14.654271 4.403194 12.012292
1430 1490 1550 1610 1670
ncomp_1 -0.595554 -1.277614 -1.447056 -1.156732 0.192146
ncomp_2 -2.267177 -21.089946 -21.170357 -4.067156 24.655519
ncomp_3 -0.491024 -31.028988 -17.978191 -0.295374 13.858413
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3
1 0.003505 0.001384 0.001461
2 0.002770 0.000164 0.002731
3 0.025464 0.029021 0.000866
4 0.012345 0.012797 0.006441
5 0.023073 0.014238 0.000008
6 0.012037 0.000182 0.004173
$weights
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.116575 0.454952 0.594281 0.822096 0.330613 0.040072 -0.078270
ncomp_2 -3.992966 -3.649706 -1.915538 1.015806 -0.429292 -0.270198 0.825464
ncomp_3 -0.622289 -0.047447 0.543203 -0.016425 0.429421 0.357572 0.613010
1430 1490 1550 1610 1670
ncomp_1 -0.316946 -0.679929 -0.770104 -0.615597 0.102257
ncomp_2 1.321732 0.510306 0.967262 2.615369 3.001763
ncomp_3 0.064875 -0.745491 0.171399 0.146985 -0.894813
$scores
ncomp_1 ncomp_2 ncomp_3
1 0.025187 0.090128 -0.000095
2 0.089624 -0.038115 0.005900
3 -0.047739 0.010300 0.012950
4 -0.072528 -0.001930 -0.003025
5 0.016320 0.030961 -0.010978
6 -0.010864 -0.091345 -0.004752
$sd_scores
ncomp_1 ncomp_2 ncomp_3
0.057603 0.061625 0.008423
$scaled_scores
ncomp_1 ncomp_2 ncomp_3
1 0.437251 1.462527 -0.011263
2 1.555890 -0.618495 0.700418
3 -0.828759 0.167148 1.537372
4 -1.259101 -0.031320 -0.359072
5 0.283322 0.502414 -1.303287
6 -0.188604 -1.482275 -0.564168
$y_loadings
ncomp_1 ncomp_2 ncomp_3
1.879041 6.978608 14.000399
$x_loadings
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.769440 0.730084 0.667992 0.573994 0.525438 0.441987 0.368035
ncomp_2 0.212412 0.257161 0.282631 0.348036 0.307298 0.292438 0.303434
ncomp_3 -3.374841 -3.214912 -3.090273 -3.214642 -2.950259 -2.821246 -2.711226
1430 1490 1550 1610 1670
ncomp_1 0.262809 0.210212 0.174189 0.176653 0.154416
ncomp_2 0.296089 0.292215 0.300681 0.330619 0.412770
ncomp_3 -3.368785 -3.248076 -3.061965 -3.136585 -3.457570
$fitted_y
ncomp_1 ncomp_2 ncomp_3
1 0.496443 1.125410 1.124082
2 0.617523 0.351537 0.434136
3 0.359412 0.431295 0.612595
4 0.312833 0.299363 0.257019
5 0.479782 0.695848 0.542153
6 0.428702 -0.208758 -0.275289
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.600980 1.173557
ncomp_2 2 0.419797 0.665199
ncomp_3 3 0.402893 0.545918
$y_quantiles
0% 25% 50% 75% 100%
0.030649 0.140000 0.227023 0.400000 1.670000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3
pls_var 0.008980 0.004282 0.008421
x_expl_var 0.361819 0.172516 0.339312
x_expl_var_cum 0.361819 0.534334 0.873646
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3
y_explained_variance 0.031418 0.527398 0.564693
Standard extended partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 4
$method$type
[1] "standard"
$method$min_w
[1] 3
$method$max_w
[1] 15
$intercept
[1] 0.419307
$x_means
1013 1073 1133 1193 1253 1313 1373 1433
0.184221 0.170189 0.163743 0.188614 0.164468 0.154311 0.190692 0.293802
1493 1553 1613 1673
0.313087 0.294753 0.286851 0.298774
$projection_m
1013 1073 1133 1193 1253 1313 1373
ncomp_1 -0.418111 -0.393132 -0.335584 -0.210762 -0.163479 -0.053445 0.051150
ncomp_2 -0.326380 -0.160268 -0.043407 -0.227056 0.297561 0.464579 0.263654
ncomp_3 -0.217506 0.010696 0.042592 -0.176147 0.293015 0.373296 -0.136170
ncomp_4 -0.035852 0.209783 0.167606 -0.443381 0.259654 0.191953 -0.813858
1433 1493 1553 1613 1673
ncomp_1 0.194107 0.294480 0.341780 0.340790 0.352205
ncomp_2 -0.101833 0.124692 0.259471 0.047073 -0.598087
ncomp_3 -0.770565 -0.158443 0.380265 0.311547 0.047420
ncomp_4 -0.121660 -0.146765 0.586770 0.261340 -0.115591
$coefficients
1013 1073 1133 1193 1253 1313
ncomp_1 -1.397985 -1.314465 -1.122050 -0.704699 -0.546603 -0.178698
ncomp_2 -3.578682 -2.385286 -1.412069 -2.221760 1.441537 2.925368
ncomp_3 -9.165129 -2.110566 -0.318131 -6.745937 8.967348 12.513142
ncomp_4 -11.745025 12.985346 11.742736 -38.651424 27.651904 26.325991
1373 1433 1493 1553 1613 1673
ncomp_1 0.171024 0.649011 0.984617 1.142768 1.139456 1.177622
ncomp_2 1.932615 -0.031383 1.817743 2.876414 1.453971 -2.818467
ncomp_3 -1.564795 -19.822640 -2.251719 12.643162 9.455783 -1.600516
ncomp_4 -60.129610 -28.577259 -12.812832 54.866858 28.261698 -9.918383
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.010169 0.000264 0.000407 0.000479
2 0.025521 0.000125 0.000075 0.000268
3 0.000730 0.002455 0.002992 0.000371
4 0.052944 0.000039 0.000002 0.000234
5 0.001588 0.006850 0.005835 0.000391
6 0.033259 0.010592 0.010733 0.000107
$weights
1013 1073 1133 1193 1253 1313 1373
ncomp_1 -0.418111 -0.393132 -0.335584 -0.210762 -0.163479 -0.053445 0.051150
ncomp_2 -0.282075 -0.118609 -0.007847 -0.204722 0.314884 0.470242 0.258234
ncomp_3 -0.001971 0.116534 0.071257 -0.026204 0.096511 0.066498 -0.310282
ncomp_4 0.109958 0.202613 0.139054 -0.325297 0.063225 -0.058294 -0.722573
1433 1493 1553 1613 1673
ncomp_1 0.194107 0.294480 0.341780 0.340790 0.352205
ncomp_2 -0.122402 0.093488 0.223255 0.010961 -0.635408
ncomp_3 -0.703316 -0.240787 0.208915 0.280462 0.442385
ncomp_4 0.394904 -0.040549 0.331852 0.052488 -0.147380
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -0.049991 -0.008996 -0.005026 0.000064
2 -0.068892 0.011588 0.002051 -0.000941
3 0.017595 0.005888 0.005203 0.002783
4 0.011477 -0.018097 0.004190 -0.000526
5 0.037366 0.003426 -0.005770 0.002132
6 0.052444 0.006191 -0.000648 -0.003512
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
0.048648 0.011202 0.004643 0.002271
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -1.027601 -0.803064 -1.082356 0.028187
2 -1.416136 1.034439 0.441673 -0.414133
3 0.361691 0.525602 1.120493 1.225450
4 0.235924 -1.615485 0.902403 -0.231792
5 0.768092 0.305848 -1.242622 0.938640
6 1.078031 0.552660 -0.139591 -1.546351
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4
3.343575 6.681456 25.684088 71.959500
$x_loadings
1013 1073 1133 1193 1253 1313 1373
ncomp_1 -0.737753 -0.749350 -0.696550 -0.502196 -0.550040 -0.469651 -0.333929
ncomp_2 -3.925343 -3.834413 -3.709878 -3.954421 -3.497272 -3.319822 -3.326663
ncomp_3 -0.351854 -0.302892 -0.315975 -0.148463 -0.300024 -0.102667 -0.066322
ncomp_4 7.398923 7.940166 7.886230 7.719387 7.879080 7.423882 6.678062
1433 1493 1553 1613 1673
ncomp_1 -0.120563 -0.045102 -0.038339 -0.026100 0.051366
ncomp_2 -3.452630 -3.505351 -3.555679 -3.821269 -4.503422
ncomp_3 -1.365399 -0.474652 -0.195544 -0.090492 0.135780
ncomp_4 7.969664 7.984234 7.783016 7.958026 7.272849
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.252159 0.192051 0.062974 0.067580
2 0.188961 0.266388 0.319060 0.251375
3 0.478138 0.517479 0.651104 0.851388
4 0.457681 0.336764 0.444381 0.406497
5 0.544243 0.567135 0.418945 0.572353
6 0.594657 0.636023 0.619376 0.366646
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.328935 0.621862
ncomp_2 2 0.320306 0.582521
ncomp_3 3 0.297278 0.448896
ncomp_4 4 0.248320 0.282420
$y_quantiles
0% 25% 50% 75% 100%
0.040000 0.208907 0.333467 0.500000 1.100000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
pls_var 0.005915 0.020778 0.000056 0.003639
x_expl_var 0.192300 0.675540 0.001820 0.118312
x_expl_var_cum 0.192300 0.867840 0.869660 0.987972
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
y_explained_variance 0.196483 0.238088 0.343704 0.542073
NIRWise PLUS extended partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 5
$method$type
[1] "nwp"
$method$min_w
[1] 2
$method$max_w
[1] 4
$intercept
[1] 0.977476
$x_means
1016 1076 1136 1196 1256 1316 1376 1436
0.183416 0.169482 0.164733 0.188919 0.163803 0.154460 0.193686 0.297633
1496 1556 1616 1676
0.312787 0.293906 0.286310 0.301280
$projection_m
1016 1076 1136 1196 1256 1316
ncomp_1 10.99720 9.206372 5.530345 2.511024 -3.248548 -3.964291
ncomp_2 32.98797 18.680438 10.099446 9.537460 -44.642168 -48.743529
ncomp_3 55.53113 2.562654 -25.297222 -47.603246 -34.143380 4.425610
ncomp_4 105.22652 -9.589389 -69.941558 -87.172573 -49.764102 57.528040
ncomp_5 194.92663 34.378816 -160.958122 -370.614311 182.818376 193.899170
1376 1436 1496 1556 1616 1676
ncomp_1 -3.555773 1.330205 -8.590435 -8.571253 -3.335553 1.690703
ncomp_2 -27.362021 40.996624 1.698698 -9.555761 0.312035 15.990803
ncomp_3 19.805750 95.639122 -18.361149 -28.474052 -26.164130 2.078910
ncomp_4 73.317238 24.630652 -77.346949 -7.565285 -1.988504 42.665904
ncomp_5 -200.035342 20.803824 -316.804417 211.340168 164.149250 46.095954
$coefficients
1016 1076 1136 1196 1256 1316
ncomp_1 10.99720 9.206372 5.530345 2.511024 -3.248548 -3.964291
ncomp_2 43.98518 27.886809 15.629792 12.048484 -47.890716 -52.707820
ncomp_3 99.51631 30.449464 -9.667431 -35.554763 -82.034096 -48.282210
ncomp_4 204.74284 20.860075 -79.608989 -122.727335 -131.798198 9.245831
ncomp_5 399.66947 55.238891 -240.567111 -493.341646 51.020179 203.145000
1376 1436 1496 1556 1616 1676
ncomp_1 -3.555773 1.330205 -8.590435 -8.571253 -3.335553 1.690703
ncomp_2 -30.917794 42.326829 -6.891737 -18.127014 -3.023518 17.681506
ncomp_3 -11.112044 137.965951 -25.252886 -46.601066 -29.187649 19.760416
ncomp_4 62.205194 162.596603 -102.599835 -54.166351 -31.176153 62.426320
ncomp_5 -137.830148 183.400426 -419.404251 157.173817 132.973098 108.522274
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.004045 0.003410 0.000091 0.000092 0
2 0.031425 0.000003 0.000003 0.000089 0
3 0.000148 0.006903 0.001362 0.000266 0
4 0.046393 0.004236 0.000258 0.000062 0
5 0.003516 0.000207 0.002606 0.000031 0
6 0.022391 0.007967 0.003735 0.000009 0
$weights
1016 1076 1136 1196 1256 1316
ncomp_1 10.99720 9.206372 5.530345 2.511024 -3.248548 -3.964291
ncomp_2 18.54200 6.586910 2.834762 6.238969 -40.374861 -43.536020
ncomp_3 21.48371 -16.037273 -35.226824 -57.599714 14.590017 57.540916
ncomp_4 46.11545 -8.192702 -38.280639 -31.710854 -9.844194 53.074605
ncomp_5 -56.97731 56.977314 0.000000 -170.931943 341.863886 113.954629
1376 1436 1496 1556 1616 1676
ncomp_1 -3.555773 1.330205 -8.590435 -8.571253 -3.335553 1.690703
ncomp_2 -22.691143 39.249261 12.983129 1.703471 4.693630 13.769888
ncomp_3 49.317946 50.507759 -22.206055 -19.841627 -27.271881 -15.256971
ncomp_4 50.176818 -86.678315 -61.516969 20.551881 25.992137 40.312780
ncomp_5 -341.863886 -113.954629 -170.931943 227.909257 170.931943 -56.977314
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.848757 0.650340 0.542192 0.231429 0.479806
2 0.861759 -0.956568 -0.031451 -0.098645 -0.472570
3 -0.334757 -0.494497 -0.512657 -0.252108 0.816544
4 0.021270 0.807861 -0.884756 0.099926 -0.395672
5 -0.566852 0.317888 0.570448 -0.690541 -0.279667
6 -0.830176 -0.325023 0.316226 0.709939 -0.148441
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.719172 0.698831 0.594303 0.472799 0.524802
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 1.180186 0.930611 0.912315 0.489488 0.914262
2 1.198264 -1.368812 -0.052921 -0.208641 -0.900473
3 -0.465476 -0.707606 -0.862619 -0.533225 1.555909
4 0.029576 1.156017 -1.488729 0.211350 -0.753946
5 -0.788201 0.454886 0.959860 -1.460538 -0.532900
6 -1.154349 -0.465096 0.532095 1.501566 -0.282852
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
5.788718 18.664359 25.100567 39.811059 147.978116
$x_loadings
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.059958 0.060414 0.055952 0.043738 0.046067 0.040006 0.030906
ncomp_2 0.052110 0.050685 0.049796 0.055058 0.048066 0.045837 0.047334
ncomp_3 -0.025402 -0.025357 -0.024767 -0.028290 -0.023877 -0.024027 -0.024732
ncomp_4 -0.022609 -0.025679 -0.025587 -0.023448 -0.025967 -0.023920 -0.019994
ncomp_5 0.005831 0.006096 0.005873 0.004821 0.006173 0.006073 0.004494
1436 1496 1556 1616 1676
ncomp_1 0.017564 0.012440 0.012566 0.012032 0.008671
ncomp_2 0.055702 0.054776 0.055061 0.058879 0.069567
ncomp_3 -0.017179 -0.025202 -0.026625 -0.029842 -0.036287
ncomp_4 -0.026576 -0.025187 -0.023650 -0.023376 -0.015701
ncomp_5 0.005874 0.005513 0.006420 0.005969 0.005776
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 1.826233 2.476573 3.018765 3.250194 3.730000
2 1.839235 0.882666 0.851215 0.752570 0.280000
3 0.642719 0.148222 -0.364436 -0.616544 0.200000
4 0.998746 1.806607 0.921851 1.021777 0.626105
5 0.410624 0.728512 1.298960 0.608419 0.328752
6 0.147301 -0.177723 0.138503 0.848441 0.700000
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 1.157807 1.903767
ncomp_2 2 0.923121 1.253427
ncomp_3 3 0.706368 0.970207
ncomp_4 4 0.524802 0.816544
ncomp_5 5 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.200000 0.280000 0.477429 0.700000 3.730000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
pls_var 0.009210 0.017038 0.002934 0.001501 0.00011
x_expl_var 0.299093 0.553310 0.095286 0.048741 0.00357
x_expl_var_cum 0.299093 0.852403 0.947689 0.996430 1.00000
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
y_explained_variance 0.27841 0.541293 0.731416 0.851745 1
The regression method is printed correctly
Code
print(round_numeric_tol(model_result))
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 3
$method$type
[1] "nwp"
$method$min_w
[1] 1
$method$max_w
[1] 3
$method$method
[1] "xls"
$intercept
[1] 1.83343
$x_means
1016 1076 1136 1196 1256 1316 1376 1436 1496 1556
0.17733 0.16393 0.15869 0.17972 0.15700 0.14838 0.18630 0.28641 0.30210 0.28336
1616 1676
0.27574 0.29097
$projection_m
1016 1076 1136 1196 1256 1316
ncomp_1 9.21288 46.71312 32.93591 -10.35171 7.80140 -2.76664
ncomp_2 20.93060 77.93060 79.03028 5.08381 -81.62068 -114.41812
ncomp_3 22.70945 160.18550 149.78004 -116.35994 -114.00190 -125.58907
1376 1436 1496 1556 1616 1676
ncomp_1 -8.30182 -13.60799 -38.85993 -20.89945 -5.20416 3.32840
ncomp_2 -96.86584 127.23952 -21.96390 -30.47003 -17.89315 53.01692
ncomp_3 -212.14988 379.64947 -18.89802 -74.33771 -87.78822 36.80028
$coefficients
1016 1076 1136 1196 1256 1316
ncomp_1 9.21288 46.71312 32.93591 -10.35171 7.80140 -2.76664
ncomp_2 30.14348 124.64372 111.96619 -5.26790 -73.81928 -117.18476
ncomp_3 52.85293 284.82922 261.74623 -121.62784 -187.82119 -242.77383
1376 1436 1496 1556 1616 1676
ncomp_1 -8.30182 -13.60799 -38.85993 -20.89945 -5.20416 3.32840
ncomp_2 -105.16767 113.63153 -60.82384 -51.36948 -23.09731 56.34532
ncomp_3 -317.31755 493.28100 -79.72186 -125.70719 -110.88553 93.14560
$n_observations
[1] 5
$x_residuals
ncomp_1 ncomp_2 ncomp_3
1 0.00044 0.00355 0.00004
2 0.00508 0.00007 0.00148
3 0.00300 0.00380 0.00013
4 0.04415 0.00729 0.00014
5 0.01110 0.00160 0.00098
$weights
1016 1076 1136 1196 1256 1316 1376
ncomp_1 9.21288 46.71312 32.93591 -10.35171 7.80140 -2.76664 -8.30182
ncomp_2 11.23963 28.79334 44.38518 15.97272 -89.82692 -111.50791 -88.13320
ncomp_3 -16.65147 12.16519 1.37903 -124.43079 34.31581 83.94803 -34.05167
1436 1496 1556 1616 1676
ncomp_1 -13.60799 -38.85993 -20.89945 -5.20416 3.32840
ncomp_2 141.55368 18.91263 -8.48602 -12.41892 49.51579
ncomp_3 148.60622 25.85990 -16.15158 -54.45547 -60.53320
$scores
ncomp_1 ncomp_2 ncomp_3
1 2.24384 0.94416 1.76006
2 1.13949 -0.79259 -0.90914
3 -2.93365 0.08120 1.35304
4 -0.54881 1.47249 -1.96698
5 0.09913 -1.70526 -0.23699
$sd_scores
ncomp_1 ncomp_2 ncomp_3
1.95260 1.28475 1.55565
$scaled_scores
ncomp_1 ncomp_2 ncomp_3
1 1.14915 0.73489 1.13140
2 0.58358 -0.61692 -0.58441
3 -1.50243 0.06321 0.86976
4 -0.28107 1.14613 -1.26441
5 0.05077 -1.32731 -0.15234
$y_loadings
ncomp_1 ncomp_2 ncomp_3
22.71813 71.29775 45.49805
$x_loadings
1016 1076 1136 1196 1256 1316 1376 1436
ncomp_1 0.01501 0.01554 0.01491 0.01274 0.01286 0.01085 0.00866 0.00403
ncomp_2 0.02459 0.02335 0.02280 0.02543 0.02086 0.02028 0.02134 0.02102
ncomp_3 -0.01076 -0.01019 -0.01002 -0.01205 -0.00986 -0.00961 -0.01020 -0.00798
1496 1556 1616 1676
ncomp_1 0.00259 0.00265 0.00252 0.00059
ncomp_2 0.02369 0.02429 0.02667 0.03560
ncomp_3 -0.01028 -0.01068 -0.01205 -0.01454
$fitted_y
ncomp_1 ncomp_2 ncomp_3
1 4.07727 5.02143 6.78149
2 2.97292 2.18033 1.27119
3 -1.10022 -1.01902 0.33403
4 1.28462 2.75710 0.79012
5 1.93256 0.22731 -0.00968
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 2.02739 2.75273
ncomp_2 2 1.56835 1.87599
ncomp_3 3 0.19918 0.29119
$y_quantiles
0% 25% 50% 75% 100%
0.22704 0.24351 0.88111 2.44250 6.83000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3
pls_var 0.00475 0.01187 0.00339
x_expl_var 0.22960 0.57341 0.16361
x_expl_var_cum 0.22960 0.80301 0.96662
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3
y_explained_variance 0.48121 0.68954 0.99499
Basic regression is printed correctly
Code
print(round_numeric(model_result))
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 4
$method$type
[1] "modified"
$intercept
[1] 1.83343
$x_means
1016 1076 1136 1196 1256 1316 1376 1436
0.177328 0.163929 0.158693 0.179722 0.156999 0.148380 0.186304 0.286410
1496 1556 1616 1676
0.302105 0.283364 0.275741 0.290975
$projection_m
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.555877 0.575107 0.568894 0.487798 0.535633 0.501824 0.435861
ncomp_2 0.501430 0.550788 0.549603 0.190868 0.431535 0.287962 -0.657071
ncomp_3 0.135317 0.428468 0.574671 -0.625727 -0.243175 -0.209174 -0.509918
ncomp_4 -0.272290 -0.173205 0.302136 -0.067441 0.021264 0.067067 0.171747
1436 1496 1556 1616 1676
ncomp_1 0.361247 0.255083 0.250436 0.229471 0.189664
ncomp_2 -0.340655 -0.501227 -0.511079 -0.531646 -0.470346
ncomp_3 0.439306 -0.026663 -0.167100 -0.383020 0.469483
ncomp_4 0.455790 -0.103133 -0.153764 -0.230423 0.076272
$coefficients
1016 1076 1136 1196 1256 1316
ncomp_1 3.745044 3.874603 3.832742 3.286381 3.608656 3.380878
ncomp_2 16.886177 18.309260 18.236342 8.288523 14.918012 10.927586
ncomp_3 90.020298 249.881683 328.826382 -329.895517 -116.509735 -102.124030
ncomp_4 35.630149 215.283898 389.178216 -343.366801 -112.262221 -88.727296
1376 1436 1496 1556 1616 1676
ncomp_1 2.936478 2.433789 1.71854 1.687229 1.545986 1.277802
ncomp_2 -14.283583 -6.493859 -11.41726 -11.706771 -12.387007 -11.048690
ncomp_3 -289.877063 230.936349 -25.82791 -102.018601 -219.396250 242.691151
ncomp_4 -255.570484 321.980728 -46.42872 -132.733132 -265.423347 257.926619
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.001173 1.5e-05 7.0e-06 0
2 0.000954 5.0e-05 5.6e-05 0
3 0.001979 8.0e-06 0.0e+00 0
4 0.001723 4.0e-06 0.0e+00 0
5 0.000527 5.8e-05 3.1e-05 0
$weights
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.555877 0.575107 0.568894 0.487798 0.535633 0.501824 0.435861
ncomp_2 0.496178 0.545353 0.544227 0.186259 0.426473 0.283220 -0.661190
ncomp_3 0.081072 0.368477 0.514752 -0.643206 -0.289201 -0.238231 -0.425482
ncomp_4 -0.210019 -0.210019 0.210019 0.210019 0.210019 0.210019 0.210019
1436 1496 1556 1616 1676
ncomp_1 0.361247 0.255083 0.250436 0.229471 0.189664
ncomp_2 -0.344069 -0.503637 -0.513445 -0.533814 -0.472138
ncomp_3 0.484634 0.036859 -0.102440 -0.316114 0.528522
ncomp_4 0.210019 -0.210019 -0.210019 -0.210019 -0.210019
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.142952 0.048033 0.004546 0.001590
2 -0.039774 0.042596 -0.001462 -0.004565
3 -0.227482 -0.060013 0.002938 -0.000336
4 0.260547 -0.057954 -0.002168 -0.000086
5 -0.136243 0.027338 -0.003855 0.003398
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
0.200133 0.054381 0.003571 0.002959
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.714287 0.883274 1.273164 0.537286
2 -0.198739 0.783289 -0.409309 -1.542539
3 -1.136656 -1.103571 0.822935 -0.113677
4 1.301872 -1.065695 -0.607101 -0.029165
5 -0.680764 0.502703 -1.079688 1.148096
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4
6.737181 26.207299 540.466088 199.750614
$x_loadings
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.228927 0.225581 0.220401 0.229336 0.200811 0.187635 0.183541
ncomp_2 0.132058 0.161904 0.147503 0.038584 0.105077 0.049716 -0.032420
ncomp_3 0.352575 0.212074 0.083182 -0.271189 -0.246537 -0.307854 -0.348843
ncomp_4 -0.977279 -0.230772 0.182203 0.053009 0.344407 0.503158 0.312273
1436 1496 1556 1616 1676
ncomp_1 0.152606 0.163765 0.167840 0.183382 0.226833
ncomp_2 -0.159622 -0.243577 -0.250051 -0.288581 -0.462489
ncomp_3 0.316924 0.067653 0.052326 -0.065874 0.399999
ncomp_4 0.802042 -0.224541 -0.406996 -0.494720 -0.230063
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 2.796525 4.055352 6.512379 6.830000
2 1.565464 2.681793 1.891884 0.980000
3 0.300841 -1.271948 0.316201 0.249000
4 3.588785 2.069974 0.898353 0.881112
5 0.915535 1.631979 -0.451668 0.227038
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 2.470824 4.033475
ncomp_2 2 2.018373 2.774648
ncomp_3 3 0.591158 0.911884
ncomp_4 4 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.227038 0.243509 0.881112 2.442500 6.830000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
pls_var 0.019107 0.001555 0.000010 0.000023
x_expl_var 0.923221 0.075157 0.000492 0.001130
x_expl_var_cum 0.923221 0.998378 0.998870 1.000000
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
y_explained_variance 0.229459 0.485821 0.955892 1
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Modified partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 5
$method$type
[1] "modified"
$intercept
[1] 0.255678
$x_means
1001 1061 1121 1181 1241 1301 1361 1421
0.156301 0.141979 0.132416 0.154116 0.139626 0.128845 0.154316 0.243516
1481 1541 1601 1661
0.283892 0.269643 0.259751 0.256310
$projection_m
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.386056 0.376287 0.373894 0.465212 0.430333 0.432307 0.467938
ncomp_2 -0.221344 -0.290215 -0.336661 -0.207807 -0.325815 -0.413097 -0.486687
ncomp_3 0.305650 0.313763 -0.318586 0.438165 -0.125121 -0.541374 -0.541512
ncomp_4 -0.212852 -0.167362 -0.266566 0.477972 0.300118 0.096730 0.102746
ncomp_5 -0.143109 0.169607 0.115804 0.241869 -0.127278 -0.176347 -0.176138
1421 1481 1541 1601 1661
ncomp_1 0.587879 0.618185 0.621539 0.611514 0.567892
ncomp_2 0.583240 0.589496 0.581114 0.548176 0.371549
ncomp_3 0.444650 0.298386 0.580720 -0.026668 -0.785578
ncomp_4 -0.313264 0.106308 0.254067 0.198561 -0.541332
ncomp_5 -0.115708 -0.086607 -0.053844 0.208091 0.083054
$coefficients
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.103782 0.101155 0.100512 0.125061 0.115685 0.116215 0.125794
ncomp_2 -0.144160 -0.223933 -0.276604 -0.107718 -0.249282 -0.346522 -0.419376
ncomp_3 4.501119 4.544642 -5.118488 6.551527 -2.150876 -8.574340 -8.649288
ncomp_4 1.456464 2.150675 -8.931479 13.388482 2.142037 -7.190704 -7.179602
ncomp_5 -4.187651 8.839861 -4.364233 22.927640 -2.877720 -14.145698 -14.126364
1421 1481 1541 1601 1661
ncomp_1 0.158037 0.166184 0.167085 0.164391 0.152664
ncomp_2 0.811361 0.826517 0.818029 0.778438 0.568860
ncomp_3 7.569162 5.361394 9.643821 0.373143 -11.370375
ncomp_4 3.088199 6.882036 13.278020 3.213374 -19.113641
ncomp_5 -1.475245 3.466301 11.154465 11.420359 -15.838032
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.001674 1.5e-05 6.0e-06 5e-06 0
2 0.000067 7.2e-05 2.4e-05 0e+00 0
3 0.003582 3.6e-05 5.0e-06 0e+00 0
4 0.002193 2.4e-05 2.3e-05 0e+00 0
5 0.000950 6.4e-05 1.1e-05 4e-06 0
6 0.001454 6.3e-05 3.5e-05 0e+00 0
$weights
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.386056 0.376287 0.373894 0.465212 0.430333 0.432307 0.467938
ncomp_2 -0.305944 -0.372674 -0.418596 -0.309753 -0.420117 -0.507832 -0.589230
ncomp_3 0.344863 0.348386 -0.286516 0.488263 -0.085231 -0.505444 -0.504531
ncomp_4 -0.318826 -0.287908 -0.218463 0.340892 0.298581 0.196606 0.191611
ncomp_5 -0.155027 0.155027 0.155027 0.155027 -0.155027 -0.155027 -0.155027
1421 1481 1541 1601 1661
ncomp_1 0.587879 0.618185 0.621539 0.611514 0.567892
ncomp_2 0.454413 0.454028 0.444911 0.414170 0.247102
ncomp_3 0.548811 0.406767 0.689129 0.078855 -0.694225
ncomp_4 -0.310361 0.152552 0.220102 0.328246 -0.231915
ncomp_5 -0.155027 -0.155027 -0.155027 0.155027 0.155027
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.175124 -0.052980 -0.002623 0.000554 0.000977
2 0.044461 0.006160 0.011080 0.003636 -0.000125
3 -0.349461 0.072248 -0.005045 0.001648 0.000264
4 0.381650 0.060541 0.000179 -0.003554 -0.000136
5 0.091422 -0.042239 -0.007126 0.002046 -0.000823
6 -0.343196 -0.043731 0.003535 -0.004331 -0.000157
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.292084 0.055545 0.006609 0.003219 0.000593
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.599565 -0.953819 -0.396936 0.172177 1.646273
2 0.152221 0.110907 1.676498 1.129560 -0.211287
3 -1.196438 1.300713 -0.763316 0.512031 0.445556
4 1.306643 1.089938 0.027082 -1.103807 -0.228606
5 0.312999 -0.760437 -1.078140 0.635439 -1.387179
6 -1.174990 -0.787302 0.534812 -1.345400 -0.264756
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.268825 1.120165 15.198028 14.304093 39.439320
$x_loadings
1001 1061 1121 1181 1241 1301 1361
ncomp_1 0.188171 0.191643 0.189747 0.196015 0.181856 0.172154 0.161319
ncomp_2 -0.342646 -0.332390 -0.307079 -0.160167 -0.183955 -0.143261 -0.065515
ncomp_3 0.636215 0.236118 -0.006184 0.062703 -0.116423 -0.227503 -0.233810
ncomp_4 -0.962673 -0.375127 -0.111364 0.450249 0.399319 0.208065 0.215325
ncomp_5 -0.518083 0.205320 0.261137 1.517559 -0.086519 -0.599734 -0.647469
1421 1481 1541 1601 1661
ncomp_1 0.156664 0.148181 0.146546 0.151717 0.171470
ncomp_2 0.137285 0.202995 0.217735 0.220092 0.250606
ncomp_3 0.088125 0.075157 0.077565 -0.017979 -0.420755
ncomp_4 -0.053937 0.282731 0.080441 0.073131 -0.449658
ncomp_5 -0.010474 -1.138156 -0.185400 0.374263 0.906366
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.302756 0.243410 0.203539 0.211468 0.25000
2 0.267631 0.274531 0.442929 0.494945 0.49000
3 0.161734 0.242665 0.165992 0.189571 0.20000
4 0.358276 0.426091 0.428811 0.377981 0.37263
5 0.280255 0.232941 0.124646 0.153908 0.12144
6 0.163419 0.114433 0.168153 0.106197 0.10000
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.128954 0.222369
ncomp_2 2 0.112951 0.215469
ncomp_3 3 0.051657 0.068153
ncomp_4 4 0.023406 0.038532
ncomp_5 5 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.10000 0.12144 0.22500 0.37263 0.49000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
pls_var 0.030345 0.001929 0.000034 0.000019 2.0e-06
x_expl_var 0.938630 0.059665 0.001056 0.000586 6.3e-05
x_expl_var_cum 0.938630 0.998295 0.999351 0.999937 1.0e+00
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
y_explained_variance 0.270475 0.44031 0.882935 0.975967 1
Standard partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 4
$method$type
[1] "standard"
$intercept
[1] 12.05516
$x_means
1004 1064 1124 1184 1244 1304 1364 1424
0.221025 0.206133 0.196139 0.218410 0.199299 0.186575 0.211677 0.305766
1484 1544 1604 1664
0.338529 0.322845 0.316359 0.319857
$projection_m
1004 1064 1124 1184 1244 1304 1364
ncomp_1 -0.352506 -0.352012 -0.342202 -0.319507 -0.308179 -0.292365 -0.268522
ncomp_2 -0.208437 -0.297937 -0.317715 -0.131081 -0.134116 -0.138987 -0.046493
ncomp_3 -0.094642 -0.118608 -0.103898 0.005833 0.166656 0.090884 0.097811
ncomp_4 0.686131 -0.026768 -0.319786 -0.520137 0.043020 -0.004351 0.166010
1424 1484 1544 1604 1664
ncomp_1 -0.222842 -0.214231 -0.225276 -0.245329 -0.271285
ncomp_2 0.568720 0.474654 0.309223 0.223243 0.131239
ncomp_3 0.773159 0.305979 -0.067272 -0.296723 -0.595707
ncomp_4 0.360298 0.149876 0.026407 0.031964 -0.545586
$coefficients
1004 1064 1124 1184 1244 1304
ncomp_1 -4.909466 -4.902584 -4.76596 -4.449889 -4.292108 -4.071867
ncomp_2 -14.049616 -17.967426 -18.69806 -10.197931 -10.173213 -10.166574
ncomp_3 -78.991197 -99.353351 -89.99024 -6.195663 104.182650 52.196261
ncomp_4 958.658631 -139.835718 -573.60915 -792.810271 169.242025 45.615704
1364 1424 1484 1544 1604 1664
ncomp_1 -3.739793 -3.103599 -2.983672 -3.137501 -3.416783 -3.778283
ncomp_2 -5.778568 21.835314 17.830370 10.422225 6.372639 1.976669
ncomp_3 61.336980 552.359901 227.786244 -35.738321 -197.232362 -406.784398
ncomp_4 312.397436 1097.246636 454.446557 4.198222 -148.891955 -1231.885826
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.000073 0.000008 0.0e+00 0e+00
2 0.000189 0.000164 1.3e-05 0e+00
3 0.000025 0.000014 6.0e-06 6e-06
4 0.000288 0.000031 2.9e-05 0e+00
5 0.004131 0.000006 1.0e-06 1e-06
6 0.002893 0.000056 2.0e-06 1e-06
$weights
1004 1064 1124 1184 1244 1304 1364
ncomp_1 -0.352506 -0.352012 -0.342202 -0.319507 -0.308179 -0.292365 -0.268522
ncomp_2 -0.196115 -0.285633 -0.305753 -0.119913 -0.123343 -0.128767 -0.037107
ncomp_3 0.002683 0.020508 0.044453 0.067039 0.229279 0.155782 0.119520
ncomp_4 0.735042 0.034528 -0.266091 -0.523152 -0.043109 -0.051321 0.115461
1424 1484 1544 1604 1664
ncomp_1 -0.222842 -0.214231 -0.225276 -0.245329 -0.271285
ncomp_2 0.576509 0.482142 0.317097 0.231818 0.140722
ncomp_3 0.507607 0.084348 -0.211658 -0.400962 -0.656987
ncomp_4 -0.039272 -0.008255 0.061174 0.185312 -0.237723
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -0.652409 -0.008325 -0.002518 0.000000
2 0.017218 0.009497 0.009570 -0.003512
3 0.168564 -0.004393 -0.002978 -0.001101
4 0.064331 0.016437 0.004680 0.005253
5 0.232242 -0.058922 -0.001895 0.000273
6 0.170055 0.045707 -0.006859 -0.000913
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
0.329042 0.034670 0.005989 0.002900
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -1.982757 -0.240119 -0.420422 0.000014
2 0.052327 0.273932 1.597916 -1.211047
3 0.512288 -0.126721 -0.497208 -0.379815
4 0.195509 0.474091 0.781498 1.811392
5 0.705813 -1.699537 -0.316436 0.094236
6 0.516821 1.318354 -1.145348 -0.314779
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4
13.92734 43.85098 686.17779 1512.32130
$x_loadings
1004 1064 1124 1184 1244 1304 1364
ncomp_1 -0.345650 -0.342027 -0.331514 -0.315316 -0.303867 -0.287864 -0.267225
ncomp_2 -0.197368 -0.295209 -0.326510 -0.151215 -0.230401 -0.201506 -0.092915
ncomp_3 -0.377189 0.002664 0.181970 0.337405 0.251558 0.182304 0.059849
ncomp_4 0.704817 0.051731 -0.240292 -0.505120 -0.021775 -0.071157 0.081431
1424 1484 1544 1604 1664
ncomp_1 -0.242994 -0.231085 -0.236361 -0.253432 -0.276204
ncomp_2 0.339492 0.442758 0.415927 0.419040 0.447489
ncomp_3 0.527903 0.088615 -0.243272 -0.496732 -0.534131
ncomp_4 -0.107514 0.039901 0.145769 0.236409 -0.342154
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 2.968836 2.603784 0.876079 0.87614
2 12.294958 12.711417 19.277984 13.96655
3 14.402809 14.210155 12.166901 10.50110
4 12.951117 13.671878 16.883407 24.82784
5 15.289670 12.705862 11.405482 11.81878
6 14.423582 16.427876 11.721119 10.34056
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 6.445988 11.684936
ncomp_2 2 6.264140 10.964174
ncomp_3 3 4.727772 7.752645
ncomp_4 4 1.765347 3.301101
$y_quantiles
0% 25% 50% 75% 100%
0.93000 7.20000 12.56746 14.43000 24.63605
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
pls_var 0.108401 0.001464 0.000045 0.000009
x_expl_var 0.986173 0.013319 0.000413 0.000079
x_expl_var_cum 0.986173 0.999493 0.999906 0.999985
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
y_explained_variance 0.335737 0.372687 0.642666 0.950178
NIRWise PLUS partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 5
$method$type
[1] "nwp"
$intercept
[1] 0.645529
$x_means
1007 1067 1127 1187 1247 1307 1367 1427
0.203432 0.187614 0.176879 0.198057 0.176160 0.163493 0.191022 0.280387
1487 1547 1607 1667
0.307658 0.290943 0.282915 0.287492
$projection_m
1007 1067 1127 1187 1247 1307
ncomp_1 -0.771415 -0.803827 -0.821552 -0.762773 -0.825493 -0.833042
ncomp_2 0.408081 -1.540140 -2.380717 1.056392 -3.136545 -3.361961
ncomp_3 11.359377 7.538915 1.841580 13.792588 -15.389603 -13.788223
ncomp_4 -18.103238 -16.391062 18.407872 17.245724 -8.436534 19.138751
ncomp_5 -1.321629 -1.113247 -1.049927 2.905569 -2.168114 2.151139
1367 1427 1487 1547 1607 1667
ncomp_1 -0.807784 -0.711102 -0.666442 -0.661056 -0.663381 -0.678925
ncomp_2 -3.485638 2.612674 2.813504 3.069369 2.910322 3.888454
ncomp_3 -15.092057 -7.832673 -6.343380 0.055951 -2.188173 16.097858
ncomp_4 -15.388645 -58.979379 -54.969402 39.178013 10.689167 65.571415
ncomp_5 1.854712 0.641378 0.710483 1.704556 -2.574289 -1.243071
$coefficients
1007 1067 1127 1187 1247 1307
ncomp_1 -0.771415 -0.803827 -0.821552 -0.762773 -0.825493 -0.833042
ncomp_2 -0.363335 -2.343967 -3.202269 0.293619 -3.962038 -4.195004
ncomp_3 10.996042 5.194948 -1.360688 14.086207 -19.351641 -17.983227
ncomp_4 -7.107196 -11.196114 17.047184 31.331931 -27.788175 1.155525
ncomp_5 -8.428825 -12.309360 15.997257 34.237500 -29.956289 3.306663
1367 1427 1487 1547 1607 1667
ncomp_1 -0.807784 -0.711102 -0.666442 -0.661056 -0.663381 -0.678925
ncomp_2 -4.293422 1.901572 2.147062 2.408313 2.246941 3.209529
ncomp_3 -19.385479 -5.931101 -4.196318 2.464264 0.058768 19.307387
ncomp_4 -34.774124 -64.910480 -59.165720 41.642278 10.747935 84.878803
ncomp_5 -32.919412 -64.269102 -58.455237 43.346834 8.173646 83.635732
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.000282 0.000019 1.1e-05 1e-05 0
2 0.000160 0.000143 4.0e-06 4e-06 0
3 0.000075 0.000053 1.2e-05 2e-06 0
4 0.001254 0.000111 1.0e-06 0e+00 0
5 0.001158 0.000009 6.0e-06 1e-06 0
6 0.000233 0.000020 1.0e-06 1e-06 0
$weights
1007 1067 1127 1187 1247 1307
ncomp_1 -0.771415 -0.803827 -0.821552 -0.762773 -0.825493 -0.833042
ncomp_2 -0.179670 -2.152586 -3.006667 0.475225 -3.765499 -3.996667
ncomp_3 9.002929 9.120367 5.114709 10.121504 -10.571743 -8.522210
ncomp_4 -36.102434 -28.524871 15.848990 -4.720158 18.632644 43.343044
ncomp_5 -1.988343 -1.988343 -1.988343 1.988343 -1.988343 1.988343
1367 1427 1487 1547 1607 1667
ncomp_1 -0.807784 -0.711102 -0.666442 -0.661056 -0.663381 -0.678925
ncomp_2 -4.101099 2.070876 2.305734 2.565702 2.404883 3.371173
ncomp_3 -9.522297 -14.598702 -13.434023 -7.549642 -9.471656 6.774679
ncomp_4 10.976964 -42.796820 -41.379160 41.746290 17.093636 40.650018
ncomp_5 1.988343 1.988343 1.988343 1.988343 -1.988343 -1.988343
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 -0.293017 -0.119415 0.108964 0.083420 -0.015482
2 -0.340266 0.100386 0.303067 -0.058447 0.009731
3 0.033201 -0.069739 -0.145714 0.328965 0.007758
4 -0.226583 0.237061 -0.298024 -0.118167 -0.002410
5 0.137690 -0.285454 -0.091637 -0.234544 0.004185
6 0.688975 0.137162 0.123343 -0.001228 -0.003781
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.386711 0.192715 0.217892 0.193685 0.009297
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 -0.757716 -0.619643 0.500084 0.430702 -1.665229
2 -0.879898 0.520901 1.390906 -0.301762 1.046627
3 0.085854 -0.361877 -0.668743 1.698456 0.834489
4 -0.585922 1.230110 -1.367759 -0.610098 -0.259243
5 0.356054 -1.481222 -0.420563 -1.210960 0.450085
6 1.781627 0.711731 0.566075 -0.006338 -0.406729
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1.044348 8.370523 26.564290 116.537933 111.488775
$x_loadings
1007 1067 1127 1187 1247 1307 1367
ncomp_1 -0.137043 -0.135264 -0.130153 -0.134465 -0.117562 -0.106943 -0.101084
ncomp_2 -0.024532 -0.035390 -0.038883 -0.019936 -0.027786 -0.024830 -0.012436
ncomp_3 0.021183 0.008959 0.000247 0.020023 -0.005650 -0.011475 -0.005068
ncomp_4 -0.004362 -0.001620 0.000815 -0.001236 0.000331 0.003061 0.000441
ncomp_5 -0.066891 -0.042576 -0.037801 0.162538 -0.012846 0.002107 0.043478
1427 1487 1547 1607 1667
ncomp_1 -0.094558 -0.087373 -0.084663 -0.088106 -0.100729
ncomp_2 0.036112 0.049101 0.046169 0.049066 0.039353
ncomp_3 -0.005734 -0.007359 -0.007781 -0.008835 -0.001053
ncomp_4 -0.004056 -0.002539 0.002750 0.001336 0.005352
ncomp_5 0.009474 0.013766 0.019029 -0.057118 -0.035307
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.352512 0.233097 0.342062 0.425482 0.410000
2 0.305263 0.405648 0.708716 0.650269 0.660000
3 0.678730 0.608991 0.463277 0.792242 0.800000
4 0.418947 0.656008 0.357984 0.239817 0.237407
5 0.783219 0.497765 0.406127 0.171583 0.175768
6 1.334504 1.471666 1.595009 1.593781 1.590000
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.349595 0.607452
ncomp_2 2 0.291680 0.418601
ncomp_3 3 0.193908 0.336723
ncomp_4 4 0.009297 0.015482
ncomp_5 5 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.175768 0.237407 0.535000 0.800000 1.590000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
pls_var 0.022316 0.000561 0.000064 0.000004 0.000004
x_expl_var 0.972452 0.024453 0.002785 0.000154 0.000156
x_expl_var_cum 0.972452 0.996905 0.999690 0.999844 1.000000
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
y_explained_variance 0.550281 0.686942 0.861643 0.999682 1
Modified extended partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 3
$method$type
[1] "modified"
$method$min_w
[1] 5
$method$max_w
[1] 10
$intercept
[1] 0.449116
$x_means
1010 1070 1130 1190 1250 1310 1370 1430
0.186961 0.171753 0.162385 0.182015 0.161207 0.150650 0.181972 0.279759
1490 1550 1610 1670
0.303068 0.284918 0.275373 0.281642
$projection_m
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.116575 0.454952 0.594281 0.822096 0.330613 0.040072 -0.078270
ncomp_2 -3.418721 -1.408624 1.011876 5.065428 1.199299 -0.072803 0.439909
ncomp_3 -0.791997 -0.209842 0.450545 0.008957 0.404531 0.345416 0.649225
1430 1490 1550 1610 1670
ncomp_1 -0.316946 -0.679929 -0.770104 -0.615597 0.102257
ncomp_2 -0.239535 -2.839009 -2.826251 -0.417049 3.505480
ncomp_3 0.126864 -0.709911 0.228005 0.269405 -0.771200
$coefficients
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.219049 0.854873 1.116678 1.544751 0.621235 0.075298 -0.147072
ncomp_2 -23.638862 -8.975362 8.178167 36.894390 8.990673 -0.432765 2.922878
ncomp_3 -34.727129 -11.913234 14.485976 37.019795 14.654271 4.403194 12.012292
1430 1490 1550 1610 1670
ncomp_1 -0.595554 -1.277614 -1.447056 -1.156732 0.192146
ncomp_2 -2.267177 -21.089946 -21.170357 -4.067156 24.655519
ncomp_3 -0.491024 -31.028988 -17.978191 -0.295374 13.858413
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3
1 0.003505 0.001384 0.001461
2 0.002770 0.000164 0.002731
3 0.025464 0.029021 0.000866
4 0.012345 0.012797 0.006441
5 0.023073 0.014238 0.000008
6 0.012037 0.000182 0.004173
$weights
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.116575 0.454952 0.594281 0.822096 0.330613 0.040072 -0.078270
ncomp_2 -3.992966 -3.649706 -1.915538 1.015806 -0.429292 -0.270198 0.825464
ncomp_3 -0.622289 -0.047447 0.543203 -0.016425 0.429421 0.357572 0.613010
1430 1490 1550 1610 1670
ncomp_1 -0.316946 -0.679929 -0.770104 -0.615597 0.102257
ncomp_2 1.321732 0.510306 0.967262 2.615369 3.001763
ncomp_3 0.064875 -0.745491 0.171399 0.146985 -0.894813
$scores
ncomp_1 ncomp_2 ncomp_3
1 0.025187 0.090128 -0.000095
2 0.089624 -0.038115 0.005900
3 -0.047739 0.010300 0.012950
4 -0.072528 -0.001930 -0.003025
5 0.016320 0.030961 -0.010978
6 -0.010864 -0.091345 -0.004752
$sd_scores
ncomp_1 ncomp_2 ncomp_3
0.057603 0.061625 0.008423
$scaled_scores
ncomp_1 ncomp_2 ncomp_3
1 0.437251 1.462527 -0.011263
2 1.555890 -0.618495 0.700418
3 -0.828759 0.167148 1.537372
4 -1.259101 -0.031320 -0.359072
5 0.283322 0.502414 -1.303287
6 -0.188604 -1.482275 -0.564168
$y_loadings
ncomp_1 ncomp_2 ncomp_3
1.879041 6.978608 14.000399
$x_loadings
1010 1070 1130 1190 1250 1310 1370
ncomp_1 0.769440 0.730084 0.667992 0.573994 0.525438 0.441987 0.368035
ncomp_2 0.212412 0.257161 0.282631 0.348036 0.307298 0.292438 0.303434
ncomp_3 -3.374841 -3.214912 -3.090273 -3.214642 -2.950259 -2.821246 -2.711226
1430 1490 1550 1610 1670
ncomp_1 0.262809 0.210212 0.174189 0.176653 0.154416
ncomp_2 0.296089 0.292215 0.300681 0.330619 0.412770
ncomp_3 -3.368785 -3.248076 -3.061965 -3.136585 -3.457570
$fitted_y
ncomp_1 ncomp_2 ncomp_3
1 0.496443 1.125410 1.124082
2 0.617523 0.351537 0.434136
3 0.359412 0.431295 0.612595
4 0.312833 0.299363 0.257019
5 0.479782 0.695848 0.542153
6 0.428702 -0.208758 -0.275289
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.600980 1.173557
ncomp_2 2 0.419797 0.665199
ncomp_3 3 0.402893 0.545918
$y_quantiles
0% 25% 50% 75% 100%
0.030649 0.140000 0.227023 0.400000 1.670000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3
pls_var 0.008980 0.004282 0.008421
x_expl_var 0.361819 0.172516 0.339312
x_expl_var_cum 0.361819 0.534334 0.873646
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3
y_explained_variance 0.031418 0.527398 0.564693
Standard extended partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 4
$method$type
[1] "standard"
$method$min_w
[1] 3
$method$max_w
[1] 15
$intercept
[1] 0.419307
$x_means
1013 1073 1133 1193 1253 1313 1373 1433
0.184221 0.170189 0.163743 0.188614 0.164468 0.154311 0.190692 0.293802
1493 1553 1613 1673
0.313087 0.294753 0.286851 0.298774
$projection_m
1013 1073 1133 1193 1253 1313 1373
ncomp_1 -0.418111 -0.393132 -0.335584 -0.210762 -0.163479 -0.053445 0.051150
ncomp_2 -0.326380 -0.160268 -0.043407 -0.227056 0.297561 0.464579 0.263654
ncomp_3 -0.217506 0.010696 0.042592 -0.176147 0.293015 0.373296 -0.136170
ncomp_4 -0.035852 0.209783 0.167606 -0.443381 0.259654 0.191953 -0.813858
1433 1493 1553 1613 1673
ncomp_1 0.194107 0.294480 0.341780 0.340790 0.352205
ncomp_2 -0.101833 0.124692 0.259471 0.047073 -0.598087
ncomp_3 -0.770565 -0.158443 0.380265 0.311547 0.047420
ncomp_4 -0.121660 -0.146765 0.586770 0.261340 -0.115591
$coefficients
1013 1073 1133 1193 1253 1313
ncomp_1 -1.397985 -1.314465 -1.122050 -0.704699 -0.546603 -0.178698
ncomp_2 -3.578682 -2.385286 -1.412069 -2.221760 1.441537 2.925368
ncomp_3 -9.165129 -2.110566 -0.318131 -6.745937 8.967348 12.513142
ncomp_4 -11.745025 12.985346 11.742736 -38.651424 27.651904 26.325991
1373 1433 1493 1553 1613 1673
ncomp_1 0.171024 0.649011 0.984617 1.142768 1.139456 1.177622
ncomp_2 1.932615 -0.031383 1.817743 2.876414 1.453971 -2.818467
ncomp_3 -1.564795 -19.822640 -2.251719 12.643162 9.455783 -1.600516
ncomp_4 -60.129610 -28.577259 -12.812832 54.866858 28.261698 -9.918383
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.010169 0.000264 0.000407 0.000479
2 0.025521 0.000125 0.000075 0.000268
3 0.000730 0.002455 0.002992 0.000371
4 0.052944 0.000039 0.000002 0.000234
5 0.001588 0.006850 0.005835 0.000391
6 0.033259 0.010592 0.010733 0.000107
$weights
1013 1073 1133 1193 1253 1313 1373
ncomp_1 -0.418111 -0.393132 -0.335584 -0.210762 -0.163479 -0.053445 0.051150
ncomp_2 -0.282075 -0.118609 -0.007847 -0.204722 0.314884 0.470242 0.258234
ncomp_3 -0.001971 0.116534 0.071257 -0.026204 0.096511 0.066498 -0.310282
ncomp_4 0.109958 0.202613 0.139054 -0.325297 0.063225 -0.058294 -0.722573
1433 1493 1553 1613 1673
ncomp_1 0.194107 0.294480 0.341780 0.340790 0.352205
ncomp_2 -0.122402 0.093488 0.223255 0.010961 -0.635408
ncomp_3 -0.703316 -0.240787 0.208915 0.280462 0.442385
ncomp_4 0.394904 -0.040549 0.331852 0.052488 -0.147380
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -0.049991 -0.008996 -0.005026 0.000064
2 -0.068892 0.011588 0.002051 -0.000941
3 0.017595 0.005888 0.005203 0.002783
4 0.011477 -0.018097 0.004190 -0.000526
5 0.037366 0.003426 -0.005770 0.002132
6 0.052444 0.006191 -0.000648 -0.003512
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
0.048648 0.011202 0.004643 0.002271
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 -1.027601 -0.803064 -1.082356 0.028187
2 -1.416136 1.034439 0.441673 -0.414133
3 0.361691 0.525602 1.120493 1.225450
4 0.235924 -1.615485 0.902403 -0.231792
5 0.768092 0.305848 -1.242622 0.938640
6 1.078031 0.552660 -0.139591 -1.546351
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4
3.343575 6.681456 25.684088 71.959500
$x_loadings
1013 1073 1133 1193 1253 1313 1373
ncomp_1 -0.737753 -0.749350 -0.696550 -0.502196 -0.550040 -0.469651 -0.333929
ncomp_2 -3.925343 -3.834413 -3.709878 -3.954421 -3.497272 -3.319822 -3.326663
ncomp_3 -0.351854 -0.302892 -0.315975 -0.148463 -0.300024 -0.102667 -0.066322
ncomp_4 7.398923 7.940166 7.886230 7.719387 7.879080 7.423882 6.678062
1433 1493 1553 1613 1673
ncomp_1 -0.120563 -0.045102 -0.038339 -0.026100 0.051366
ncomp_2 -3.452630 -3.505351 -3.555679 -3.821269 -4.503422
ncomp_3 -1.365399 -0.474652 -0.195544 -0.090492 0.135780
ncomp_4 7.969664 7.984234 7.783016 7.958026 7.272849
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.252159 0.192051 0.062974 0.067580
2 0.188961 0.266388 0.319060 0.251375
3 0.478138 0.517479 0.651104 0.851388
4 0.457681 0.336764 0.444381 0.406497
5 0.544243 0.567135 0.418945 0.572353
6 0.594657 0.636023 0.619376 0.366646
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 0.328935 0.621862
ncomp_2 2 0.320306 0.582521
ncomp_3 3 0.297278 0.448896
ncomp_4 4 0.248320 0.282420
$y_quantiles
0% 25% 50% 75% 100%
0.040000 0.208907 0.333467 0.500000 1.100000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
pls_var 0.005915 0.020778 0.000056 0.003639
x_expl_var 0.192300 0.675540 0.001820 0.118312
x_expl_var_cum 0.192300 0.867840 0.869660 0.987972
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
y_explained_variance 0.196483 0.238088 0.343704 0.542073
NIRWise PLUS extended partial least squares computes the correct results
Code
round_numeric(model_result)
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 5
$method$type
[1] "nwp"
$method$min_w
[1] 2
$method$max_w
[1] 4
$intercept
[1] 0.977476
$x_means
1016 1076 1136 1196 1256 1316 1376 1436
0.183416 0.169482 0.164733 0.188919 0.163803 0.154460 0.193686 0.297633
1496 1556 1616 1676
0.312787 0.293906 0.286310 0.301280
$projection_m
1016 1076 1136 1196 1256 1316
ncomp_1 10.99720 9.206372 5.530345 2.511024 -3.248548 -3.964291
ncomp_2 32.98797 18.680438 10.099446 9.537460 -44.642168 -48.743529
ncomp_3 55.53113 2.562654 -25.297222 -47.603246 -34.143380 4.425610
ncomp_4 105.22652 -9.589389 -69.941558 -87.172573 -49.764102 57.528040
ncomp_5 194.92663 34.378816 -160.958122 -370.614311 182.818376 193.899170
1376 1436 1496 1556 1616 1676
ncomp_1 -3.555773 1.330205 -8.590435 -8.571253 -3.335553 1.690703
ncomp_2 -27.362021 40.996624 1.698698 -9.555761 0.312035 15.990803
ncomp_3 19.805750 95.639122 -18.361149 -28.474052 -26.164130 2.078910
ncomp_4 73.317238 24.630652 -77.346949 -7.565285 -1.988504 42.665904
ncomp_5 -200.035342 20.803824 -316.804417 211.340168 164.149250 46.095954
$coefficients
1016 1076 1136 1196 1256 1316
ncomp_1 10.99720 9.206372 5.530345 2.511024 -3.248548 -3.964291
ncomp_2 43.98518 27.886809 15.629792 12.048484 -47.890716 -52.707820
ncomp_3 99.51631 30.449464 -9.667431 -35.554763 -82.034096 -48.282210
ncomp_4 204.74284 20.860075 -79.608989 -122.727335 -131.798198 9.245831
ncomp_5 399.66947 55.238891 -240.567111 -493.341646 51.020179 203.145000
1376 1436 1496 1556 1616 1676
ncomp_1 -3.555773 1.330205 -8.590435 -8.571253 -3.335553 1.690703
ncomp_2 -30.917794 42.326829 -6.891737 -18.127014 -3.023518 17.681506
ncomp_3 -11.112044 137.965951 -25.252886 -46.601066 -29.187649 19.760416
ncomp_4 62.205194 162.596603 -102.599835 -54.166351 -31.176153 62.426320
ncomp_5 -137.830148 183.400426 -419.404251 157.173817 132.973098 108.522274
$n_observations
[1] 6
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.004045 0.003410 0.000091 0.000092 0
2 0.031425 0.000003 0.000003 0.000089 0
3 0.000148 0.006903 0.001362 0.000266 0
4 0.046393 0.004236 0.000258 0.000062 0
5 0.003516 0.000207 0.002606 0.000031 0
6 0.022391 0.007967 0.003735 0.000009 0
$weights
1016 1076 1136 1196 1256 1316
ncomp_1 10.99720 9.206372 5.530345 2.511024 -3.248548 -3.964291
ncomp_2 18.54200 6.586910 2.834762 6.238969 -40.374861 -43.536020
ncomp_3 21.48371 -16.037273 -35.226824 -57.599714 14.590017 57.540916
ncomp_4 46.11545 -8.192702 -38.280639 -31.710854 -9.844194 53.074605
ncomp_5 -56.97731 56.977314 0.000000 -170.931943 341.863886 113.954629
1376 1436 1496 1556 1616 1676
ncomp_1 -3.555773 1.330205 -8.590435 -8.571253 -3.335553 1.690703
ncomp_2 -22.691143 39.249261 12.983129 1.703471 4.693630 13.769888
ncomp_3 49.317946 50.507759 -22.206055 -19.841627 -27.271881 -15.256971
ncomp_4 50.176818 -86.678315 -61.516969 20.551881 25.992137 40.312780
ncomp_5 -341.863886 -113.954629 -170.931943 227.909257 170.931943 -56.977314
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 0.848757 0.650340 0.542192 0.231429 0.479806
2 0.861759 -0.956568 -0.031451 -0.098645 -0.472570
3 -0.334757 -0.494497 -0.512657 -0.252108 0.816544
4 0.021270 0.807861 -0.884756 0.099926 -0.395672
5 -0.566852 0.317888 0.570448 -0.690541 -0.279667
6 -0.830176 -0.325023 0.316226 0.709939 -0.148441
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
0.719172 0.698831 0.594303 0.472799 0.524802
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 1.180186 0.930611 0.912315 0.489488 0.914262
2 1.198264 -1.368812 -0.052921 -0.208641 -0.900473
3 -0.465476 -0.707606 -0.862619 -0.533225 1.555909
4 0.029576 1.156017 -1.488729 0.211350 -0.753946
5 -0.788201 0.454886 0.959860 -1.460538 -0.532900
6 -1.154349 -0.465096 0.532095 1.501566 -0.282852
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
5.788718 18.664359 25.100567 39.811059 147.978116
$x_loadings
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.059958 0.060414 0.055952 0.043738 0.046067 0.040006 0.030906
ncomp_2 0.052110 0.050685 0.049796 0.055058 0.048066 0.045837 0.047334
ncomp_3 -0.025402 -0.025357 -0.024767 -0.028290 -0.023877 -0.024027 -0.024732
ncomp_4 -0.022609 -0.025679 -0.025587 -0.023448 -0.025967 -0.023920 -0.019994
ncomp_5 0.005831 0.006096 0.005873 0.004821 0.006173 0.006073 0.004494
1436 1496 1556 1616 1676
ncomp_1 0.017564 0.012440 0.012566 0.012032 0.008671
ncomp_2 0.055702 0.054776 0.055061 0.058879 0.069567
ncomp_3 -0.017179 -0.025202 -0.026625 -0.029842 -0.036287
ncomp_4 -0.026576 -0.025187 -0.023650 -0.023376 -0.015701
ncomp_5 0.005874 0.005513 0.006420 0.005969 0.005776
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
1 1.826233 2.476573 3.018765 3.250194 3.730000
2 1.839235 0.882666 0.851215 0.752570 0.280000
3 0.642719 0.148222 -0.364436 -0.616544 0.200000
4 0.998746 1.806607 0.921851 1.021777 0.626105
5 0.410624 0.728512 1.298960 0.608419 0.328752
6 0.147301 -0.177723 0.138503 0.848441 0.700000
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 1.157807 1.903767
ncomp_2 2 0.923121 1.253427
ncomp_3 3 0.706368 0.970207
ncomp_4 4 0.524802 0.816544
ncomp_5 5 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.200000 0.280000 0.477429 0.700000 3.730000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
pls_var 0.009210 0.017038 0.002934 0.001501 0.00011
x_expl_var 0.299093 0.553310 0.095286 0.048741 0.00357
x_expl_var_cum 0.299093 0.852403 0.947689 0.996430 1.00000
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4 ncomp_5
y_explained_variance 0.27841 0.541293 0.731416 0.851745 1
The regression method is printed correctly
Code
print(round_numeric_tol(model_result))
Output
$method
$method$fit_method
[1] "xlsr"
$method$ncomp
[1] 3
$method$type
[1] "nwp"
$method$min_w
[1] 1
$method$max_w
[1] 3
$method$method
[1] "xls"
$intercept
[1] 1.83343
$x_means
1016 1076 1136 1196 1256 1316 1376 1436 1496 1556
0.17733 0.16393 0.15869 0.17972 0.15700 0.14838 0.18630 0.28641 0.30210 0.28336
1616 1676
0.27574 0.29097
$projection_m
1016 1076 1136 1196 1256 1316
ncomp_1 9.21288 46.71312 32.93591 -10.35171 7.80140 -2.76664
ncomp_2 20.93060 77.93060 79.03028 5.08381 -81.62068 -114.41812
ncomp_3 22.70945 160.18550 149.78004 -116.35994 -114.00190 -125.58907
1376 1436 1496 1556 1616 1676
ncomp_1 -8.30182 -13.60799 -38.85993 -20.89945 -5.20416 3.32840
ncomp_2 -96.86584 127.23952 -21.96390 -30.47003 -17.89315 53.01692
ncomp_3 -212.14988 379.64947 -18.89802 -74.33771 -87.78822 36.80028
$coefficients
1016 1076 1136 1196 1256 1316
ncomp_1 9.21288 46.71312 32.93591 -10.35171 7.80140 -2.76664
ncomp_2 30.14348 124.64372 111.96619 -5.26790 -73.81928 -117.18476
ncomp_3 52.85293 284.82922 261.74623 -121.62784 -187.82119 -242.77383
1376 1436 1496 1556 1616 1676
ncomp_1 -8.30182 -13.60799 -38.85993 -20.89945 -5.20416 3.32840
ncomp_2 -105.16767 113.63153 -60.82384 -51.36948 -23.09731 56.34532
ncomp_3 -317.31755 493.28100 -79.72186 -125.70719 -110.88553 93.14560
$n_observations
[1] 5
$x_residuals
ncomp_1 ncomp_2 ncomp_3
1 0.00044 0.00355 0.00004
2 0.00508 0.00007 0.00148
3 0.00300 0.00380 0.00013
4 0.04415 0.00729 0.00014
5 0.01110 0.00160 0.00098
$weights
1016 1076 1136 1196 1256 1316 1376
ncomp_1 9.21288 46.71312 32.93591 -10.35171 7.80140 -2.76664 -8.30182
ncomp_2 11.23963 28.79334 44.38518 15.97272 -89.82692 -111.50791 -88.13320
ncomp_3 -16.65147 12.16519 1.37903 -124.43079 34.31581 83.94803 -34.05167
1436 1496 1556 1616 1676
ncomp_1 -13.60799 -38.85993 -20.89945 -5.20416 3.32840
ncomp_2 141.55368 18.91263 -8.48602 -12.41892 49.51579
ncomp_3 148.60622 25.85990 -16.15158 -54.45547 -60.53320
$scores
ncomp_1 ncomp_2 ncomp_3
1 2.24384 0.94416 1.76006
2 1.13949 -0.79259 -0.90914
3 -2.93365 0.08120 1.35304
4 -0.54881 1.47249 -1.96698
5 0.09913 -1.70526 -0.23699
$sd_scores
ncomp_1 ncomp_2 ncomp_3
1.95260 1.28475 1.55565
$scaled_scores
ncomp_1 ncomp_2 ncomp_3
1 1.14915 0.73489 1.13140
2 0.58358 -0.61692 -0.58441
3 -1.50243 0.06321 0.86976
4 -0.28107 1.14613 -1.26441
5 0.05077 -1.32731 -0.15234
$y_loadings
ncomp_1 ncomp_2 ncomp_3
22.71813 71.29775 45.49805
$x_loadings
1016 1076 1136 1196 1256 1316 1376 1436
ncomp_1 0.01501 0.01554 0.01491 0.01274 0.01286 0.01085 0.00866 0.00403
ncomp_2 0.02459 0.02335 0.02280 0.02543 0.02086 0.02028 0.02134 0.02102
ncomp_3 -0.01076 -0.01019 -0.01002 -0.01205 -0.00986 -0.00961 -0.01020 -0.00798
1496 1556 1616 1676
ncomp_1 0.00259 0.00265 0.00252 0.00059
ncomp_2 0.02369 0.02429 0.02667 0.03560
ncomp_3 -0.01028 -0.01068 -0.01205 -0.01454
$fitted_y
ncomp_1 ncomp_2 ncomp_3
1 4.07727 5.02143 6.78149
2 2.97292 2.18033 1.27119
3 -1.10022 -1.01902 0.33403
4 1.28462 2.75710 0.79012
5 1.93256 0.22731 -0.00968
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 2.02739 2.75273
ncomp_2 2 1.56835 1.87599
ncomp_3 3 0.19918 0.29119
$y_quantiles
0% 25% 50% 75% 100%
0.22704 0.24351 0.88111 2.44250 6.83000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3
pls_var 0.00475 0.01187 0.00339
x_expl_var 0.22960 0.57341 0.16361
x_expl_var_cum 0.22960 0.80301 0.96662
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3
y_explained_variance 0.48121 0.68954 0.99499
Basic regression is printed correctly
Code
print(round_numeric(model_result))
Output
$method
$method$fit_method
[1] "plsr"
$method$ncomp
[1] 4
$method$type
[1] "modified"
$intercept
[1] 1.83343
$x_means
1016 1076 1136 1196 1256 1316 1376 1436
0.177328 0.163929 0.158693 0.179722 0.156999 0.148380 0.186304 0.286410
1496 1556 1616 1676
0.302105 0.283364 0.275741 0.290975
$projection_m
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.555877 0.575107 0.568894 0.487798 0.535633 0.501824 0.435861
ncomp_2 0.501430 0.550788 0.549603 0.190868 0.431535 0.287962 -0.657071
ncomp_3 0.135317 0.428468 0.574671 -0.625727 -0.243175 -0.209174 -0.509918
ncomp_4 -0.272290 -0.173205 0.302136 -0.067441 0.021264 0.067067 0.171747
1436 1496 1556 1616 1676
ncomp_1 0.361247 0.255083 0.250436 0.229471 0.189664
ncomp_2 -0.340655 -0.501227 -0.511079 -0.531646 -0.470346
ncomp_3 0.439306 -0.026663 -0.167100 -0.383020 0.469483
ncomp_4 0.455790 -0.103133 -0.153764 -0.230423 0.076272
$coefficients
1016 1076 1136 1196 1256 1316
ncomp_1 3.745044 3.874603 3.832742 3.286381 3.608656 3.380878
ncomp_2 16.886177 18.309260 18.236342 8.288523 14.918012 10.927586
ncomp_3 90.020298 249.881683 328.826382 -329.895517 -116.509735 -102.124030
ncomp_4 35.630149 215.283898 389.178216 -343.366801 -112.262221 -88.727296
1376 1436 1496 1556 1616 1676
ncomp_1 2.936478 2.433789 1.71854 1.687229 1.545986 1.277802
ncomp_2 -14.283583 -6.493859 -11.41726 -11.706771 -12.387007 -11.048690
ncomp_3 -289.877063 230.936349 -25.82791 -102.018601 -219.396250 242.691151
ncomp_4 -255.570484 321.980728 -46.42872 -132.733132 -265.423347 257.926619
$x_residuals
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.001173 1.5e-05 7.0e-06 0
2 0.000954 5.0e-05 5.6e-05 0
3 0.001979 8.0e-06 0.0e+00 0
4 0.001723 4.0e-06 0.0e+00 0
5 0.000527 5.8e-05 3.1e-05 0
$weights
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.555877 0.575107 0.568894 0.487798 0.535633 0.501824 0.435861
ncomp_2 0.496178 0.545353 0.544227 0.186259 0.426473 0.283220 -0.661190
ncomp_3 0.081072 0.368477 0.514752 -0.643206 -0.289201 -0.238231 -0.425482
ncomp_4 -0.210019 -0.210019 0.210019 0.210019 0.210019 0.210019 0.210019
1436 1496 1556 1616 1676
ncomp_1 0.361247 0.255083 0.250436 0.229471 0.189664
ncomp_2 -0.344069 -0.503637 -0.513445 -0.533814 -0.472138
ncomp_3 0.484634 0.036859 -0.102440 -0.316114 0.528522
ncomp_4 0.210019 -0.210019 -0.210019 -0.210019 -0.210019
$scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.142952 0.048033 0.004546 0.001590
2 -0.039774 0.042596 -0.001462 -0.004565
3 -0.227482 -0.060013 0.002938 -0.000336
4 0.260547 -0.057954 -0.002168 -0.000086
5 -0.136243 0.027338 -0.003855 0.003398
$sd_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
0.200133 0.054381 0.003571 0.002959
$scaled_scores
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 0.714287 0.883274 1.273164 0.537286
2 -0.198739 0.783289 -0.409309 -1.542539
3 -1.136656 -1.103571 0.822935 -0.113677
4 1.301872 -1.065695 -0.607101 -0.029165
5 -0.680764 0.502703 -1.079688 1.148096
$y_loadings
ncomp_1 ncomp_2 ncomp_3 ncomp_4
6.737181 26.207299 540.466088 199.750614
$x_loadings
1016 1076 1136 1196 1256 1316 1376
ncomp_1 0.228927 0.225581 0.220401 0.229336 0.200811 0.187635 0.183541
ncomp_2 0.132058 0.161904 0.147503 0.038584 0.105077 0.049716 -0.032420
ncomp_3 0.352575 0.212074 0.083182 -0.271189 -0.246537 -0.307854 -0.348843
ncomp_4 -0.977279 -0.230772 0.182203 0.053009 0.344407 0.503158 0.312273
1436 1496 1556 1616 1676
ncomp_1 0.152606 0.163765 0.167840 0.183382 0.226833
ncomp_2 -0.159622 -0.243577 -0.250051 -0.288581 -0.462489
ncomp_3 0.316924 0.067653 0.052326 -0.065874 0.399999
ncomp_4 0.802042 -0.224541 -0.406996 -0.494720 -0.230063
$fitted_y
ncomp_1 ncomp_2 ncomp_3 ncomp_4
1 2.796525 4.055352 6.512379 6.830000
2 1.565464 2.681793 1.891884 0.980000
3 0.300841 -1.271948 0.316201 0.249000
4 3.588785 2.069974 0.898353 0.881112
5 0.915535 1.631979 -0.451668 0.227038
$cal_error
ncomp cal_set_error max_residuals
ncomp_1 1 2.470824 4.033475
ncomp_2 2 2.018373 2.774648
ncomp_3 3 0.591158 0.911884
ncomp_4 4 0.000000 0.000000
$y_quantiles
0% 25% 50% 75% 100%
0.227038 0.243509 0.881112 2.442500 6.830000
$explained_variance
$explained_variance$x_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
pls_var 0.019107 0.001555 0.000010 0.000023
x_expl_var 0.923221 0.075157 0.000492 0.001130
x_expl_var_cum 0.923221 0.998378 0.998870 1.000000
$explained_variance$y_variance
ncomp_1 ncomp_2 ncomp_3 ncomp_4
y_explained_variance 0.229459 0.485821 0.955892 1
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