SemiParamBernsteinDepCS: Semiparametric Bayesian Regression for Dependent Current Status Data

Implements a semiparametric Bayesian regression framework using Bernstein polynomial baseline models for analyzing dependent current status data. The package accommodates proportional hazards (PH) and proportional odds (PO) regression models with Archimedean copulas ('Gumbel', 'Frank', and 'Clayton') to model the joint dependence structure between event and observation or censoring times. Estimation is performed using a Robust Adaptive Metropolis (RAM) Markov Chain Monte Carlo ('MCMC') algorithm. Model comparison metrics including Deviance Information Criterion ('DIC') and posterior summaries with Highest Posterior Density ('HPD') intervals and Kendall's tau are provided. Methodological details are described in Sharma and Balakrishnan (2026) <doi:10.1080/02664763.2026.2701921>.

Version:	0.1.0
Depends:	R (≥ 4.0.0)
Imports:	stats, graphics
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-08-07
DOI:	10.32614/CRAN.package.SemiParamBernsteinDepCS
Author:	Shikhar Tyagi [aut, cre], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer:	Shikhar Tyagi <shikhar1093tyagi at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
Language:	en-US
CRAN checks:	SemiParamBernsteinDepCS results

Documentation:

Reference manual:	SemiParamBernsteinDepCS.html , SemiParamBernsteinDepCS.pdf
Vignettes:	Semiparametric Bayesian Regression for Dependent Current Status Data (source, R code)

Downloads:

Package source:	SemiParamBernsteinDepCS_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: SemiParamBernsteinDepCS_0.1.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): SemiParamBernsteinDepCS_0.1.0.tgz, r-oldrel (arm64): SemiParamBernsteinDepCS_0.1.0.tgz, r-release (x86_64): SemiParamBernsteinDepCS_0.1.0.tgz, r-oldrel (x86_64): SemiParamBernsteinDepCS_0.1.0.tgz

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