{ "_id": "6a16aa20acfb0bcc41d83ea4", "Package": "GLMcat", "Title": "Generalized Linear Models for Categorical Responses", "Version": "0.2.7", "Authors@R": "c(person(given = \"Lorena\", family = \"León\",role = c(\"aut\", \"cre\"), email = \"ylorenaleonv@gmail.com\"),\nperson(given = \"Jean\", family = \"Peyhardi\", email = \"jean.peyhardi@umontpellier.fr\", role = \"aut\"),\nperson(given = \"Catherine\", family = \"Trottier\", email = \"catherine.trottier@umontpellier.fr\", role = \"aut\"))", "Description": "In statistical modeling, there is a wide variety of\nregression models for categorical dependent variables (nominal\nor ordinal data); yet, there is no software embracing all these\nmodels together in a uniform and generalized format. Following\nthe methodology proposed by Peyhardi, Trottier, and Guédon\n(2015) , we introduce 'GLMcat', an R\npackage to estimate generalized linear models implemented under\nthe unified specification (r, F, Z). Where r represents the\nratio of probabilities (reference, cumulative, adjacent, or\nsequential), F the cumulative cdf function for the linkage, and\nZ, the design matrix.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.2.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "URL": "https://github.com/ylleonv/GLMcat", "BugReports": "https://github.com/ylleonv/GLMcat/issues", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://ylleonv.r-universe.dev", "Date/Publication": "2024-09-19 09:28:15 UTC", "RemoteUrl": "https://github.com/ylleonv/glmcat", "RemoteRef": "HEAD", "RemoteSha": "c923a6137df3f1746be2c6f07e6cbf3919673bde", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-27 08:13:30 UTC", "User": "root" }, "Author": "Lorena León [aut, cre],\nJean Peyhardi [aut],\nCatherine Trottier [aut]", "Maintainer": "Lorena León ", "MD5sum": "ef3ea73f99e8721ef8866433760b6ad2", "_user": "ylleonv", "_type": "src", "_file": 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"control_glmcat" ] }, { "page": "discrete_cm", "title": "Discrete Choice Models", "topics": [ "discrete_cm" ] }, { "page": "DisturbedDreams", "title": "Severity of disturbed dreams", "topics": [ "DisturbedDreams" ] }, { "page": "extractAIC", "title": "Extract AIC from a fitted 'glmcat' model object", "topics": [ "extractAIC.glmcat" ] }, { "page": "glmcat", "title": "Generalized linear models for categorical responses", "topics": [ "glmcat" ] }, { "page": "logLik", "title": "Log-likelihood of a fitted 'glmcat' model object", "topics": [ "logLik.glmcat" ] }, { "page": "nobs", "title": "Number of observations of a fitted 'glmcat' model object", "topics": [ "nobs.glmcat" ] }, { "page": "plot", "title": "Plot method for a fitted 'glmcat' model object", "topics": [ "plot.glmcat" ] }, { "page": "predict", "title": "Predict method for a a fitted 'glmcat' model object", "topics": [ "predict.glmcat" ] }, { "page": "print.anova", "title": "Printing Anova for 'glmcat' model fits", "topics": [ "print.anova.glmcat" ] }, { "page": "print", "title": "Print method for a fitted 'glmcat' model object", "topics": [ "print.glmcat" ] }, { "page": "print.summary.glmcat", "title": "Printing a fitted 'glmcat' model object", "topics": [ "print.summary.glmcat" ] }, { "page": "step", "title": "Stepwise for a 'glmcat' model object", "topics": [ "step.glmcat" ] }, { "page": "summary", "title": "Summary method for a fitted 'glmcat' model object", "topics": [ "summary.glmcat" ] }, { "page": "terms", "title": "Terms of a fitted 'glmcat' model object", "topics": [ "terms.glmcat" ] }, { "page": "TravelChoice", "title": "Travel Mode Choice", "topics": [ "TravelChoice" ] }, { "page": "vcov", "title": "Variance-Covariance Matrix for a fitted 'glmcat' model object", "topics": [ "vcov.glmcat" ] } ], "_readme": "https://github.com/ylleonv/glmcat/raw/HEAD/README.md", "_rundeps": [ "BH", "cli", "glue", "lattice", "lifecycle", "magrittr", "MASS", "Matrix", "nlme", "numDeriv", "ordinal", "Rcpp", 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