DESCRIPTION

Type: Package
Package: gofcat
Title: Goodness-of-Fit Measures for Categorical Response Models
Version: 0.1.3
Authors@R: 
    person(given = "Ejike R.",
           family = "Ugba",
           role = c("aut", "cre", "cph"),
           email = "ejike.ugba@outlook.com",
           comment = c(ORCID = "0000-0003-2572-0023"))
Description: 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>.
License: GPL-2 | file LICENSE
URL: https://github.com/ejikeugba/gofcat
BugReports: https://github.com/ejikeugba/gofcat/issues
Depends:
    R (>= 3.2.0)
Imports:
    utils,
    crayon,
    stats,
    Matrix,
    epiR,
    reshape,
    stringr,
    VGAM (>= 1.1-4)
Encoding: UTF-8
LazyData: True
RoxygenNote: 7.1.2
Suggests:
    serp,
    dfidx,
    mlogit,
    nnet,
    ordinal,
    MASS,
    testthat,
    covr