{ "_id": "6ab7a84a99f7aa8c6aa3372d", "Package": "FitVerse", "Type": "Package", "Title": "Parametric Distribution Fitting and Analysis", "Version": "1.0-2", "Date": "2026-09-06", "Authors@R": "c(\nperson(\"Karuna G.\", \"Reddy\",\nemail = \"karuna.reddy@auckland.ac.nz\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-9467-4668\")),\nperson(\"M. G. M.\", \"Khan\",\nemail = \"mgm.khan@usp.ac.fj\",\nrole = \"aut\")\n)", "Description": "Provides a unified, user-friendly interface for fitting\nparametric probability distributions to continuous univariate\ndata. 'FitVerse' supports 52 distribution families spanning\nsymmetric, right-skewed, heavy-tailed, bounded, and\nextreme-value shapes, and three estimation methods: Maximum\nLikelihood Estimation (MLE), Method of Moments (MOM), and\nL-Moments (L-MOM). Automatic best-fit selection is performed\nusing AIC, BIC, and goodness-of-fit tests (Kolmogorov-Smirnov,\nAnderson-Darling, Cramer-von Mises (CvM)). Every fitted model\nproduces a publication-quality diagnostic plot: a histogram\noverlaid with the fitted density curve and the estimated PDF\nformula annotated directly on the figure. An optional\ninteractive version is produced via 'plotly'. Additional tools\ninclude bootstrap confidence intervals for parameter estimates\nand return levels, batch fitting across multiple columns for\nautomated workflows and web-upload use cases, JSON\nserialisation for integration with 'Shiny' web applications,\nand automated HTML/PDF report generation. 'FitVerse' is\ndesigned to support data characterisation in survey sampling,\nhydrology, and actuarial workflows, where identifying the\nunderlying distribution of a variable is a prerequisite for\ndownstream modelling and inference. L-moment estimation follows\nHosking (1990) and\nHosking and Wallis (1997, ISBN:9780521430456). Model selection\nvia AIC follows Akaike (1974) \nand via BIC follows Schwarz (1978)\n. 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