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tests/testthat/_snaps/validate_prediction.md
In proximetricsR: Spectral Preprocessing and Chemometric Calibration of NIR Sensors
The validation results are correct
Code
val$validation
Output
$ncomp_1
$ncomp_1$val_results
y_hat error mahalanobis q_residual
1 3.927327901 4.6726721 0.9274963704 0.8410359
2 9.294686078 -3.2846861 9.3545366460 11.2062395
3 7.098889692 0.3211103 4.8455679932 0.8998034
4 3.898462526 3.1815375 0.9059173284 0.9574533
5 1.392740956 2.3372590 0.0006997921 2.3007677
6 1.558898199 5.2711018 0.0014757365 1.1864656
7 4.833148353 1.4868516 1.7337107399 1.0642931
8 4.136265413 1.0237346 1.0912659057 1.2459077
9 3.374234516 1.4457655 0.5582103634 1.2716116
10 -0.002387304 5.0523873 0.3261791950 1.2041011
$ncomp_1$val_stats
rsq rmse max_res
0.1289977 3.4475632 5.2711018
$ncomp_2
$ncomp_2$val_results
y_hat error mahalanobis q_residual
1 3.672546 4.9274540 0.48418572 0.8120552
2 5.696587 0.3134127 8.75329875 12.0370207
3 6.076601 1.3433991 2.75181624 0.8836422
4 3.369853 3.7101471 0.54093409 0.9706488
5 1.105426 2.6245735 0.02633989 2.3280696
6 1.361863 5.4681369 0.01296089 1.1738763
7 4.017285 2.3027149 1.07642386 1.0636432
8 3.682460 1.4775396 0.61047100 1.2081569
9 3.045246 1.7747536 0.31318142 1.2342831
10 -1.202457 6.2524573 0.61651350 1.2560050
$ncomp_2$val_stats
rsq rmse max_res
0.2137245 3.7485618 6.2524573
$ncomp_3
$ncomp_3$val_results
y_hat error mahalanobis q_residual
1 5.148650 3.4513504 1.38807317 1.0678643
2 3.204192 2.8058077 8.87267302 8.7902561
3 6.300385 1.1196150 1.85902857 0.9785791
4 3.974418 3.1055820 0.53931974 1.1864733
5 1.434358 2.2956417 0.07045838 2.4421133
6 2.686727 4.1432726 0.86681184 1.5313832
7 4.464406 1.8555942 0.81535776 1.1938130
8 5.009379 0.1506209 1.26781546 1.7032898
9 4.479032 0.3409680 1.21386517 1.4640895
10 -1.059914 6.1099136 0.42094307 1.3516143
$ncomp_3$val_stats
rsq rmse max_res
0.2917607 3.2323444 6.1099136
$ncomp_4
$ncomp_4$val_results
y_hat error mahalanobis q_residual
1 8.170898 0.4291020 4.059876 0.4199535
2 6.582030 -0.5720298 10.425487 6.8784245
3 8.794807 -1.3748067 3.450715 0.4554293
4 6.793318 0.2866824 3.030741 0.7566006
5 3.893740 -0.1637405 2.051919 1.8486240
6 6.104665 0.7253345 4.511159 0.6249015
7 6.659332 -0.3393318 2.203789 0.8730503
8 8.812862 -3.6528621 5.732095 0.5007324
9 7.389985 -2.5699845 3.710974 0.7252076
10 2.685905 2.3640946 4.953065 0.6456461
$ncomp_4$val_stats
rsq rmse max_res
0.2961665 1.7853994 -3.6528621
Not available target values are correctly ignored
Code
val2$validation
Output
$ncomp_1
$ncomp_1$val_results
y_hat error mahalanobis q_residual
1 3.927327901 4.6726721 0.9274963704 0.8410359
2 9.294686078 -3.2846861 9.3545366460 11.2062395
3 7.098889692 0.3211103 4.8455679932 0.8998034
4 3.898462526 3.1815375 0.9059173284 0.9574533
5 1.392740956 2.3372590 0.0006997921 2.3007677
6 1.558898199 NA 0.0014757365 1.1864656
7 4.833148353 NA 1.7337107399 1.0642931
8 4.136265413 NA 1.0912659057 1.2459077
9 3.374234516 NA 0.5582103634 1.2716116
10 -0.002387304 NA 0.3261791950 1.2041011
$ncomp_1$val_stats
rsq rmse max_res
0.09217139 3.47530932 4.67267210
$ncomp_2
$ncomp_2$val_results
y_hat error mahalanobis q_residual
1 3.672546 4.9274540 0.48418572 0.8120552
2 5.696587 0.3134127 8.75329875 12.0370207
3 6.076601 1.3433991 2.75181624 0.8836422
4 3.369853 3.7101471 0.54093409 0.9706488
5 1.105426 2.6245735 0.02633989 2.3280696
6 1.361863 NA 0.01296089 1.1738763
7 4.017285 NA 1.07642386 1.0636432
8 3.682460 NA 0.61047100 1.2081569
9 3.045246 NA 0.31318142 1.2342831
10 -1.202457 NA 0.61651350 1.2560050
$ncomp_2$val_stats
rsq rmse max_res
0.2989971 3.4218536 4.9274540
$ncomp_3
$ncomp_3$val_results
y_hat error mahalanobis q_residual
1 5.148650 3.451350 1.38807317 1.0678643
2 3.204192 2.805808 8.87267302 8.7902561
3 6.300385 1.119615 1.85902857 0.9785791
4 3.974418 3.105582 0.53931974 1.1864733
5 1.434358 2.295642 0.07045838 2.4421133
6 2.686727 NA 0.86681184 1.5313832
7 4.464406 NA 0.81535776 1.1938130
8 5.009379 NA 1.26781546 1.7032898
9 4.479032 NA 1.21386517 1.4640895
10 -1.059914 NA 0.42094307 1.3516143
$ncomp_3$val_stats
rsq rmse max_res
0.7732385 2.9980212 3.4513504
$ncomp_4
$ncomp_4$val_results
y_hat error mahalanobis q_residual
1 8.170898 0.4291020 4.059876 0.4199535
2 6.582030 -0.5720298 10.425487 6.8784245
3 8.794807 -1.3748067 3.450715 0.4554293
4 6.793318 0.2866824 3.030741 0.7566006
5 3.893740 -0.1637405 2.051919 1.8486240
6 6.104665 NA 4.511159 0.6249015
7 6.659332 NA 2.203789 0.8730503
8 8.812862 NA 5.732095 0.5007324
9 7.389985 NA 3.710974 0.7252076
10 2.685905 NA 4.953065 0.6456461
$ncomp_4$val_stats
rsq rmse max_res
0.8541440 0.7922181 -1.3748067
Validations are correctly printed if original model grid given
Code
print(val_copy)
Output
Validating response: THCA
Number of validated predictions: 10
Units of the predicted response: %
Number of validations: 4
Number of components (nc): 1, 2, 3, 4
________________________________________________________________________________
y | nc_1 y_hat error mahalanobis q_residual
1 NA | 3.927 4.673 0.927 0.841
2 6.01 | 9.295 -3.285 9.355 11.206
3 7.42 | 7.099 0.321 4.846 0.900
4 7.08 | 3.898 3.182 0.906 0.957
5 3.73 | 1.393 2.337 0.001 2.301
6 6.83 | 1.559 5.271 0.001 1.186
7 6.32 | 4.833 1.487 1.734 1.064
8 5.16 | 4.136 1.024 1.091 1.246
9 4.82 | 3.374 1.446 0.558 1.272
10 5.05 | -0.002 5.052 0.326 1.204
--------------------------------------------------------------------------------
y | nc_2 y_hat error mahalanobis q_residual
1 NA | 3.673 4.927 0.484 0.812
2 6.01 | 5.697 0.313 8.753 12.037
3 7.42 | 6.077 1.343 2.752 0.884
4 7.08 | 3.370 3.710 0.541 0.971
5 3.73 | 1.105 2.625 0.026 2.328
6 6.83 | 1.362 5.468 0.013 1.174
7 6.32 | 4.017 2.303 1.076 1.064
8 5.16 | 3.682 1.478 0.610 1.208
9 4.82 | 3.045 1.775 0.313 1.234
10 5.05 | -1.202 6.252 0.617 1.256
--------------------------------------------------------------------------------
y | nc_3 y_hat error mahalanobis q_residual
1 NA | 5.149 3.451 1.388 1.068
2 6.01 | 3.204 2.806 8.873 8.790
3 7.42 | 6.300 1.120 1.859 0.979
4 7.08 | 3.974 3.106 0.539 1.186
5 3.73 | 1.434 2.296 0.070 2.442
6 6.83 | 2.687 4.143 0.867 1.531
7 6.32 | 4.464 1.856 0.815 1.194
8 5.16 | 5.009 0.151 1.268 1.703
9 4.82 | 4.479 0.341 1.214 1.464
10 5.05 | -1.060 6.110 0.421 1.352
--------------------------------------------------------------------------------
y | nc_4 y_hat error mahalanobis q_residual
1 NA | 8.171 0.429 4.060 0.420
2 6.01 | 6.582 -0.572 10.425 6.878
3 7.42 | 8.795 -1.375 3.451 0.455
4 7.08 | 6.793 0.287 3.031 0.757
5 3.73 | 3.894 -0.164 2.052 1.849
6 6.83 | 6.105 0.725 4.511 0.625
7 6.32 | 6.659 -0.339 2.204 0.873
8 5.16 | 8.813 -3.653 5.732 0.501
9 4.82 | 7.390 -2.570 3.711 0.725
10 5.05 | 2.686 2.364 4.953 0.646
________________________________________________________________________________
Comparison of model and validation statistics (excluding NA's):
| nc_1 val model | nc_2 val model | nc_3 val model
R^2 | 0.129 0.058 | 0.214 0.021 | 0.292 0.006
RMSE | 3.448 3.881 | 3.749 4.084 | 3.232 4.001
max_error | 5.271 11.697 | 6.252 11.634 | 6.110 11.607
--------------------------------------------------------------------------------
| nc_4 val model
R^2 | 0.296 0.001
RMSE | 1.785 3.785
max_error | -3.653 11.506
________________________________________________________________________________
Validations are correctly printed if original model grid missing
Code
print(val_copy)
Output
Validating response: THCA
Number of validated predictions: 10
Number of validations: 4
Number of components (nc): 1, 2, 3, 4
________________________________________________________________________________
y | nc_1 y_hat error mahalanobis q_residual
1 8.60 | 3.927 4.673 0.927 0.841
2 6.01 | 9.295 -3.285 9.355 11.206
3 7.42 | 7.099 0.321 4.846 0.900
4 7.08 | 3.898 3.182 0.906 0.957
5 3.73 | 1.393 2.337 0.001 2.301
6 6.83 | 1.559 5.271 0.001 1.186
7 6.32 | 4.833 1.487 1.734 1.064
8 5.16 | 4.136 1.024 1.091 1.246
9 4.82 | 3.374 1.446 0.558 1.272
10 5.05 | -0.002 5.052 0.326 1.204
--------------------------------------------------------------------------------
y | nc_2 y_hat error mahalanobis q_residual
1 8.60 | 3.673 4.927 0.484 0.812
2 6.01 | 5.697 0.313 8.753 12.037
3 7.42 | 6.077 1.343 2.752 0.884
4 7.08 | 3.370 3.710 0.541 0.971
5 3.73 | 1.105 2.625 0.026 2.328
6 6.83 | 1.362 5.468 0.013 1.174
7 6.32 | 4.017 2.303 1.076 1.064
8 5.16 | 3.682 1.478 0.610 1.208
9 4.82 | 3.045 1.775 0.313 1.234
10 5.05 | -1.202 6.252 0.617 1.256
--------------------------------------------------------------------------------
y | nc_3 y_hat error mahalanobis q_residual
1 8.60 | 5.149 3.451 1.388 1.068
2 6.01 | 3.204 2.806 8.873 8.790
3 7.42 | 6.300 1.120 1.859 0.979
4 7.08 | 3.974 3.106 0.539 1.186
5 3.73 | 1.434 2.296 0.070 2.442
6 6.83 | 2.687 4.143 0.867 1.531
7 6.32 | 4.464 1.856 0.815 1.194
8 5.16 | 5.009 0.151 1.268 1.703
9 4.82 | 4.479 0.341 1.214 1.464
10 5.05 | -1.060 6.110 0.421 1.352
--------------------------------------------------------------------------------
y | nc_4 y_hat error mahalanobis q_residual
1 8.60 | 8.171 0.429 4.060 0.420
2 6.01 | 6.582 -0.572 10.425 6.878
3 7.42 | 8.795 -1.375 3.451 0.455
4 7.08 | 6.793 0.287 3.031 0.757
5 3.73 | 3.894 -0.164 2.052 1.849
6 6.83 | 6.105 0.725 4.511 0.625
7 6.32 | 6.659 -0.339 2.204 0.873
8 5.16 | 8.813 -3.653 5.732 0.501
9 4.82 | 7.390 -2.570 3.711 0.725
10 5.05 | 2.686 2.364 4.953 0.646
________________________________________________________________________________
Comparison of model and validation statistics:
| nc_1 val | nc_2 val | nc_3 val | nc_4 val
R^2 | 0.129 | 0.214 | 0.292 | 0.296
RMSE | 3.448 | 3.749 | 3.232 | 1.785
max_error | 5.271 | 6.252 | 6.110 | -3.653
________________________________________________________________________________
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The validation results are correct
Code
val$validation
Output
$ncomp_1
$ncomp_1$val_results
y_hat error mahalanobis q_residual
1 3.927327901 4.6726721 0.9274963704 0.8410359
2 9.294686078 -3.2846861 9.3545366460 11.2062395
3 7.098889692 0.3211103 4.8455679932 0.8998034
4 3.898462526 3.1815375 0.9059173284 0.9574533
5 1.392740956 2.3372590 0.0006997921 2.3007677
6 1.558898199 5.2711018 0.0014757365 1.1864656
7 4.833148353 1.4868516 1.7337107399 1.0642931
8 4.136265413 1.0237346 1.0912659057 1.2459077
9 3.374234516 1.4457655 0.5582103634 1.2716116
10 -0.002387304 5.0523873 0.3261791950 1.2041011
$ncomp_1$val_stats
rsq rmse max_res
0.1289977 3.4475632 5.2711018
$ncomp_2
$ncomp_2$val_results
y_hat error mahalanobis q_residual
1 3.672546 4.9274540 0.48418572 0.8120552
2 5.696587 0.3134127 8.75329875 12.0370207
3 6.076601 1.3433991 2.75181624 0.8836422
4 3.369853 3.7101471 0.54093409 0.9706488
5 1.105426 2.6245735 0.02633989 2.3280696
6 1.361863 5.4681369 0.01296089 1.1738763
7 4.017285 2.3027149 1.07642386 1.0636432
8 3.682460 1.4775396 0.61047100 1.2081569
9 3.045246 1.7747536 0.31318142 1.2342831
10 -1.202457 6.2524573 0.61651350 1.2560050
$ncomp_2$val_stats
rsq rmse max_res
0.2137245 3.7485618 6.2524573
$ncomp_3
$ncomp_3$val_results
y_hat error mahalanobis q_residual
1 5.148650 3.4513504 1.38807317 1.0678643
2 3.204192 2.8058077 8.87267302 8.7902561
3 6.300385 1.1196150 1.85902857 0.9785791
4 3.974418 3.1055820 0.53931974 1.1864733
5 1.434358 2.2956417 0.07045838 2.4421133
6 2.686727 4.1432726 0.86681184 1.5313832
7 4.464406 1.8555942 0.81535776 1.1938130
8 5.009379 0.1506209 1.26781546 1.7032898
9 4.479032 0.3409680 1.21386517 1.4640895
10 -1.059914 6.1099136 0.42094307 1.3516143
$ncomp_3$val_stats
rsq rmse max_res
0.2917607 3.2323444 6.1099136
$ncomp_4
$ncomp_4$val_results
y_hat error mahalanobis q_residual
1 8.170898 0.4291020 4.059876 0.4199535
2 6.582030 -0.5720298 10.425487 6.8784245
3 8.794807 -1.3748067 3.450715 0.4554293
4 6.793318 0.2866824 3.030741 0.7566006
5 3.893740 -0.1637405 2.051919 1.8486240
6 6.104665 0.7253345 4.511159 0.6249015
7 6.659332 -0.3393318 2.203789 0.8730503
8 8.812862 -3.6528621 5.732095 0.5007324
9 7.389985 -2.5699845 3.710974 0.7252076
10 2.685905 2.3640946 4.953065 0.6456461
$ncomp_4$val_stats
rsq rmse max_res
0.2961665 1.7853994 -3.6528621
Not available target values are correctly ignored
Code
val2$validation
Output
$ncomp_1
$ncomp_1$val_results
y_hat error mahalanobis q_residual
1 3.927327901 4.6726721 0.9274963704 0.8410359
2 9.294686078 -3.2846861 9.3545366460 11.2062395
3 7.098889692 0.3211103 4.8455679932 0.8998034
4 3.898462526 3.1815375 0.9059173284 0.9574533
5 1.392740956 2.3372590 0.0006997921 2.3007677
6 1.558898199 NA 0.0014757365 1.1864656
7 4.833148353 NA 1.7337107399 1.0642931
8 4.136265413 NA 1.0912659057 1.2459077
9 3.374234516 NA 0.5582103634 1.2716116
10 -0.002387304 NA 0.3261791950 1.2041011
$ncomp_1$val_stats
rsq rmse max_res
0.09217139 3.47530932 4.67267210
$ncomp_2
$ncomp_2$val_results
y_hat error mahalanobis q_residual
1 3.672546 4.9274540 0.48418572 0.8120552
2 5.696587 0.3134127 8.75329875 12.0370207
3 6.076601 1.3433991 2.75181624 0.8836422
4 3.369853 3.7101471 0.54093409 0.9706488
5 1.105426 2.6245735 0.02633989 2.3280696
6 1.361863 NA 0.01296089 1.1738763
7 4.017285 NA 1.07642386 1.0636432
8 3.682460 NA 0.61047100 1.2081569
9 3.045246 NA 0.31318142 1.2342831
10 -1.202457 NA 0.61651350 1.2560050
$ncomp_2$val_stats
rsq rmse max_res
0.2989971 3.4218536 4.9274540
$ncomp_3
$ncomp_3$val_results
y_hat error mahalanobis q_residual
1 5.148650 3.451350 1.38807317 1.0678643
2 3.204192 2.805808 8.87267302 8.7902561
3 6.300385 1.119615 1.85902857 0.9785791
4 3.974418 3.105582 0.53931974 1.1864733
5 1.434358 2.295642 0.07045838 2.4421133
6 2.686727 NA 0.86681184 1.5313832
7 4.464406 NA 0.81535776 1.1938130
8 5.009379 NA 1.26781546 1.7032898
9 4.479032 NA 1.21386517 1.4640895
10 -1.059914 NA 0.42094307 1.3516143
$ncomp_3$val_stats
rsq rmse max_res
0.7732385 2.9980212 3.4513504
$ncomp_4
$ncomp_4$val_results
y_hat error mahalanobis q_residual
1 8.170898 0.4291020 4.059876 0.4199535
2 6.582030 -0.5720298 10.425487 6.8784245
3 8.794807 -1.3748067 3.450715 0.4554293
4 6.793318 0.2866824 3.030741 0.7566006
5 3.893740 -0.1637405 2.051919 1.8486240
6 6.104665 NA 4.511159 0.6249015
7 6.659332 NA 2.203789 0.8730503
8 8.812862 NA 5.732095 0.5007324
9 7.389985 NA 3.710974 0.7252076
10 2.685905 NA 4.953065 0.6456461
$ncomp_4$val_stats
rsq rmse max_res
0.8541440 0.7922181 -1.3748067
Validations are correctly printed if original model grid given
Code
print(val_copy)
Output
Validating response: THCA
Number of validated predictions: 10
Units of the predicted response: %
Number of validations: 4
Number of components (nc): 1, 2, 3, 4
________________________________________________________________________________
y | nc_1 y_hat error mahalanobis q_residual
1 NA | 3.927 4.673 0.927 0.841
2 6.01 | 9.295 -3.285 9.355 11.206
3 7.42 | 7.099 0.321 4.846 0.900
4 7.08 | 3.898 3.182 0.906 0.957
5 3.73 | 1.393 2.337 0.001 2.301
6 6.83 | 1.559 5.271 0.001 1.186
7 6.32 | 4.833 1.487 1.734 1.064
8 5.16 | 4.136 1.024 1.091 1.246
9 4.82 | 3.374 1.446 0.558 1.272
10 5.05 | -0.002 5.052 0.326 1.204
--------------------------------------------------------------------------------
y | nc_2 y_hat error mahalanobis q_residual
1 NA | 3.673 4.927 0.484 0.812
2 6.01 | 5.697 0.313 8.753 12.037
3 7.42 | 6.077 1.343 2.752 0.884
4 7.08 | 3.370 3.710 0.541 0.971
5 3.73 | 1.105 2.625 0.026 2.328
6 6.83 | 1.362 5.468 0.013 1.174
7 6.32 | 4.017 2.303 1.076 1.064
8 5.16 | 3.682 1.478 0.610 1.208
9 4.82 | 3.045 1.775 0.313 1.234
10 5.05 | -1.202 6.252 0.617 1.256
--------------------------------------------------------------------------------
y | nc_3 y_hat error mahalanobis q_residual
1 NA | 5.149 3.451 1.388 1.068
2 6.01 | 3.204 2.806 8.873 8.790
3 7.42 | 6.300 1.120 1.859 0.979
4 7.08 | 3.974 3.106 0.539 1.186
5 3.73 | 1.434 2.296 0.070 2.442
6 6.83 | 2.687 4.143 0.867 1.531
7 6.32 | 4.464 1.856 0.815 1.194
8 5.16 | 5.009 0.151 1.268 1.703
9 4.82 | 4.479 0.341 1.214 1.464
10 5.05 | -1.060 6.110 0.421 1.352
--------------------------------------------------------------------------------
y | nc_4 y_hat error mahalanobis q_residual
1 NA | 8.171 0.429 4.060 0.420
2 6.01 | 6.582 -0.572 10.425 6.878
3 7.42 | 8.795 -1.375 3.451 0.455
4 7.08 | 6.793 0.287 3.031 0.757
5 3.73 | 3.894 -0.164 2.052 1.849
6 6.83 | 6.105 0.725 4.511 0.625
7 6.32 | 6.659 -0.339 2.204 0.873
8 5.16 | 8.813 -3.653 5.732 0.501
9 4.82 | 7.390 -2.570 3.711 0.725
10 5.05 | 2.686 2.364 4.953 0.646
________________________________________________________________________________
Comparison of model and validation statistics (excluding NA's):
| nc_1 val model | nc_2 val model | nc_3 val model
R^2 | 0.129 0.058 | 0.214 0.021 | 0.292 0.006
RMSE | 3.448 3.881 | 3.749 4.084 | 3.232 4.001
max_error | 5.271 11.697 | 6.252 11.634 | 6.110 11.607
--------------------------------------------------------------------------------
| nc_4 val model
R^2 | 0.296 0.001
RMSE | 1.785 3.785
max_error | -3.653 11.506
________________________________________________________________________________
Validations are correctly printed if original model grid missing
Code
print(val_copy)
Output
Validating response: THCA
Number of validated predictions: 10
Number of validations: 4
Number of components (nc): 1, 2, 3, 4
________________________________________________________________________________
y | nc_1 y_hat error mahalanobis q_residual
1 8.60 | 3.927 4.673 0.927 0.841
2 6.01 | 9.295 -3.285 9.355 11.206
3 7.42 | 7.099 0.321 4.846 0.900
4 7.08 | 3.898 3.182 0.906 0.957
5 3.73 | 1.393 2.337 0.001 2.301
6 6.83 | 1.559 5.271 0.001 1.186
7 6.32 | 4.833 1.487 1.734 1.064
8 5.16 | 4.136 1.024 1.091 1.246
9 4.82 | 3.374 1.446 0.558 1.272
10 5.05 | -0.002 5.052 0.326 1.204
--------------------------------------------------------------------------------
y | nc_2 y_hat error mahalanobis q_residual
1 8.60 | 3.673 4.927 0.484 0.812
2 6.01 | 5.697 0.313 8.753 12.037
3 7.42 | 6.077 1.343 2.752 0.884
4 7.08 | 3.370 3.710 0.541 0.971
5 3.73 | 1.105 2.625 0.026 2.328
6 6.83 | 1.362 5.468 0.013 1.174
7 6.32 | 4.017 2.303 1.076 1.064
8 5.16 | 3.682 1.478 0.610 1.208
9 4.82 | 3.045 1.775 0.313 1.234
10 5.05 | -1.202 6.252 0.617 1.256
--------------------------------------------------------------------------------
y | nc_3 y_hat error mahalanobis q_residual
1 8.60 | 5.149 3.451 1.388 1.068
2 6.01 | 3.204 2.806 8.873 8.790
3 7.42 | 6.300 1.120 1.859 0.979
4 7.08 | 3.974 3.106 0.539 1.186
5 3.73 | 1.434 2.296 0.070 2.442
6 6.83 | 2.687 4.143 0.867 1.531
7 6.32 | 4.464 1.856 0.815 1.194
8 5.16 | 5.009 0.151 1.268 1.703
9 4.82 | 4.479 0.341 1.214 1.464
10 5.05 | -1.060 6.110 0.421 1.352
--------------------------------------------------------------------------------
y | nc_4 y_hat error mahalanobis q_residual
1 8.60 | 8.171 0.429 4.060 0.420
2 6.01 | 6.582 -0.572 10.425 6.878
3 7.42 | 8.795 -1.375 3.451 0.455
4 7.08 | 6.793 0.287 3.031 0.757
5 3.73 | 3.894 -0.164 2.052 1.849
6 6.83 | 6.105 0.725 4.511 0.625
7 6.32 | 6.659 -0.339 2.204 0.873
8 5.16 | 8.813 -3.653 5.732 0.501
9 4.82 | 7.390 -2.570 3.711 0.725
10 5.05 | 2.686 2.364 4.953 0.646
________________________________________________________________________________
Comparison of model and validation statistics:
| nc_1 val | nc_2 val | nc_3 val | nc_4 val
R^2 | 0.129 | 0.214 | 0.292 | 0.296
RMSE | 3.448 | 3.749 | 3.232 | 1.785
max_error | 5.271 | 6.252 | 6.110 | -3.653
________________________________________________________________________________
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