{ "_id": "6a1eea4ab401979e73411fe8", "Type": "Package", "Package": "asympDiag", "Title": "Diagnostic Tools for Asymptotic Theory", "Version": "0.3.2", "Authors@R": "c(\nperson(\"Álvaro\", \"Kothe\", , \"kothe65@gmail.com\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0003-2114-3193\")),\nperson(\"Alexandre\", \"Patriota\", role = \"aut\")\n)", "Description": "Leveraging Monte Carlo simulations, this package provides\ntools for diagnosing regression models. It implements a\nparametric bootstrap framework to compute statistics, generates\ndiagnostic envelopes to assess goodness-of-fit, and evaluates\ntype I error control for Wald tests. By simulating data under\nthe assumption that the model is true, it helps to identify\nmodel mis-specifications and enhances the reliability of the\nmodel inferences.", "License": "MIT + file LICENSE", "URL": "https://github.com/Alvaro-Kothe/asympDiag", "BugReports": "https://github.com/Alvaro-Kothe/asympDiag/issues", "Config/testthat/edition": "3", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Repository": "https://alvaro-kothe.r-universe.dev", "Date/Publication": "2026-02-15 18:26:49 UTC", "RemoteUrl": "https://github.com/alvaro-kothe/asympdiag", "RemoteRef": "HEAD", "RemoteSha": "e6f885346f605bf21210f9837cb93222d4be5862", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-19 10:07:21 UTC", "User": "root" }, "Author": "Álvaro Kothe [aut, cre, cph] (ORCID:\n),\nAlexandre Patriota [aut]", "Maintainer": "Álvaro Kothe ", "MD5sum": "28725bbb7ec36a8918152070e1c6f1d0", "_user": "alvaro-kothe", "_type": "src", "_file": "asympDiag_0.3.2.tar.gz", 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object", "topics": [ "concat_pvalues" ] }, { "page": "envelope", "title": "Generate Simulated Envelope", "topics": [ "envelope" ] }, { "page": "envelope_residual", "title": "Recommended Residuals for Envelope Plots", "topics": [ "envelope_residual", "envelope_residual.default", "envelope_residual.glm", "envelope_residual.lm" ] }, { "page": "get_converged", "title": "Did the model converged", "topics": [ "get_converged", "get_converged.default" ] }, { "page": "get_fixef", "title": "Get fixed effects", "topics": [ "get_fixef", "get_fixef.default", "get_fixef.glmmTMB", "get_fixef.merMod" ] }, { "page": "get_model_response", "title": "Extract the Response Variable from a Model Object", "topics": [ "get_model_response" ] }, { "page": "get_refit", "title": "Refit the Model", "topics": [ "get_refit" ] }, { "page": "get_vcov", "title": "Get covariance matrix", "topics": [ "get_vcov", "get_vcov.default", "get_vcov.glmmTMB" ] }, { "page": "parametric_bootstrap", "title": "Perform Parametric Bootstrap Simulations", "topics": [ "parametric_bootstrap" ] }, { "page": "plot_cook", "title": "Plot Cook's distances", "topics": [ "plot_cook" ] }, { "page": "plot_ecdf_pvalue", "title": "Plot Empirical Cumulative Distribution Function (ECDF) of p-values", "topics": [ "plot_ecdf_pvalue" ] }, { "page": "plot_res_vs_linear_predictor", "title": "Plot Residuals against Linear Predictor", "topics": [ "plot_res_vs_linear_predictor" ] }, { "page": "plot.AD_envelope", "title": "Envelope Plot", "topics": [ "plot.AD_envelope" ] }, { "page": "plot.AD_pvalues", "title": "Plot Empirical Cumulative Distribution Function (ECDF) of p-values", "topics": [ "plot.AD_pvalues" ] }, { "page": "refit_model", "title": "Refit Model", "topics": [ "refit_model" ] }, { "page": "select_covariates", "title": "Select covariates", "topics": [ "select_covariates" ] }, { "page": "simulate_wald_pvalues", "title": "Generate Wald test P-Values with Monte Carlo Simulations", "topics": [ "simulate_wald_pvalues" ] } ], 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