gofcat: Goodness-of-Fit Measures for Categorical Response Models
A post-estimation method for categorical response models (CRM).
Inputs from objects of class serp(), clm(), polr(), multinom(), mlogit(),
vglm() and glm() are currently supported. Available tests include the
Hosmer-Lemeshow tests for the binary, multinomial and ordinal logistic
regression; the Lipsitz and the Pulkstenis-Robinson tests for the ordinal
models. The proportional odds, adjacent-category, and constrained continuation-ratio
models are particularly supported at ordinal level. Tests for the proportional
odds assumptions in ordinal models are also possible with the Brant and the
Likelihood-Ratio tests. Moreover, several summary measures of predictive strength
(Pseudo R-squared), and some useful error metrics, including, the brier
score, misclassification rate and logloss are also available for the
binary, multinomial and ordinal models. Ugba, E. R. and Gertheiss, J. (2018)
<http://www.statmod.org/workshops_archive_proceedings_2018.html>.
Version: |
0.1.2 |
Depends: |
R (≥ 3.2.0) |
Imports: |
utils, crayon, stats, Matrix, epiR, reshape, stringr, VGAM (≥
1.1-4) |
Suggests: |
serp, dfidx, mlogit, nnet, ordinal, MASS, testthat, covr |
Published: |
2022-02-14 |
Author: |
Ejike R. Ugba
[aut, cre, cph] |
Maintainer: |
Ejike R. Ugba <ejike.ugba at outlook.com> |
License: |
GPL-2 |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
gofcat results |
Documentation:
Downloads:
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