BetaDanish: The Beta-Danish Distribution for Lifetime Data Analysis

Implements the four-parameter Beta-Danish distribution and its three-parameter Exponentiated Danish submodel for survival, reliability and lifetime data analysis, following Ahmad (2026), "Modeling Diverse Survival Patterns: The Development and Characterization of a New Four-Parameter Lifetime Distribution", PhD thesis, Allama Iqbal Open University. Density, distribution, quantile, survival, hazard and random generation functions are evaluated so as to retain accuracy in both tails; the upper tail is heavy, with a regularly varying survival function. Estimation covers maximum likelihood for complete and right-censored samples by a two-stage multi-start search that guarantees nesting of the submodel, with fits on the edge of the parameter space reported as such, ridge-penalized fitting for weakly identified regimes, a grouped likelihood for times recorded on a coarse grid, and Bayesian sampling by adaptive multi-chain Metropolis with convergence checks. Goodness of fit uses Kolmogorov-Smirnov, Cramer-von Mises and Anderson-Darling statistics computed on one scale for complete and censored samples. Inference provides log-scale Wald and profile likelihood intervals, together with a reparameterization in terms of the identified composite of the two shape parameters. Structural properties include raw, incomplete and conditional moments with their existence conditions, Shannon, Renyi and Tsallis entropies, mean residual life, mean deviations, Lorenz and Bonferroni curves, probability weighted moments, order statistics, stress-strength reliability, hazard shape classification, the tail index and the Kullback-Leibler separation from the submodel. Regression modules cover accelerated failure time models, mixture and promotion-time cure models with three- or four-parameter kernels, and competing risks with Aalen-Johansen comparison and Gray's test. Analyses can be run directly from a delimited text file or spreadsheet.

Version: 1.0.0
Depends: R (≥ 3.5)
Imports: grDevices, maxLik, survival, stats, graphics, utils, tools
Suggests: readxl, flexsurv, testthat (≥ 3.0.0), knitr, rmarkdown, cmprsk, coda, MCMCpack
Published: 2026-11-13
DOI: 10.32614/CRAN.package.BetaDanish
Author: Bilal Ahmad [aut, cre], Muhammad Yameen Danish [aut]
Maintainer: Bilal Ahmad <bilalahmad.imcbh9 at gmail.com>
BugReports: https://github.com/bilal-aiou/BetaDanish/issues
License: GPL-3
URL: https://bilal-aiou.github.io/BetaDanish/, https://github.com/bilal-aiou/BetaDanish
NeedsCompilation: no
Language: en-US
Citation: BetaDanish citation info
Materials: README, NEWS
CRAN checks: BetaDanish results

Documentation:

Reference manual: BetaDanish.html , BetaDanish.pdf
Vignettes: Introduction to the BetaDanish Package (source, R code)
Bayesian Estimation with BetaDanish (source, R code)
Competing Risks with the Beta-Danish Distribution (source, R code)
Analysing Your Own Data from a CSV File (source, R code)
Cure Models with the Beta-Danish Distribution (source, R code)
A Case Study Using the Beta-Danish Distribution (source, R code)

Downloads:

Package source: BetaDanish_1.0.0.tar.gz
Windows binaries: r-devel: BetaDanish_0.3.0.zip, r-release: BetaDanish_0.3.0.zip, r-oldrel: BetaDanish_0.3.0.zip
macOS binaries: r-release (arm64): BetaDanish_1.0.0.tgz, r-oldrel (arm64): BetaDanish_1.0.0.tgz, r-release (x86_64): BetaDanish_1.0.0.tgz, r-oldrel (x86_64): BetaDanish_1.0.0.tgz
Old sources: BetaDanish archive

Linking:

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