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The package offers unified predict()\nmethods, multiple variance-covariance estimators (observed\ninformation, outer product of gradients, robust/Huber-White,\ncluster-robust, bootstrap, jackknife), and a full suite of\nhypothesis tests (Wald, likelihood ratio, information matrix,\nVuong, overdispersion, and goodness-of-fit). It is fully\ncompatible with 'marginaleffects' for post-estimation analysis.\nMethods implemented include Cameron and Trivedi (1990)\n, for Poisson overdispersion\ntesting, Manjon and Martinez (2014)\n, for goodness-of-fit testing\nof count data models, Vuong (1989) , for\nnon-nested likelihood ratio testing, and White (1982)\n, for information matrix tests.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/pkgdown/logo": "man/figures/logo.png", "URL": "https://alfisankipan.github.io/mlmodels/", "BugReports": "https://github.com/alfisankipan/mlmodels/issues", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-12 11:50:40 UTC", "User": "root" }, "Author": "Alfonso Sanchez-Penalver [aut, cre] (ORCID:\n)", "Maintainer": "Alfonso Sanchez-Penalver ", "Repository": "https://cranhaven.r-universe.dev", "Date/Publication": "2026-06-12 02:02:00 UTC", "RemoteUrl": 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