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.
- Version0.1.2
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release02/14/2022
Documentation
Team
Ejike R. Ugba
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Last 30 days
This package has been downloaded 285 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 10 times.
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Last 365 days
This package has been downloaded 3,847 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was May 10, 2024 with 62 downloads.
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Dependencies
- Imports6 packages
- Suggests7 packages