TieFreeCensor: Algorithm for Generating Tie-Free Progressive Type-II Censored Samples

Generates tie-free progressive Type-II censored samples from discrete distributions and user-specified discrete probability mass functions (PMF) or cumulative distribution functions (CDF). Provides maximum likelihood estimation (MLE), Bayesian estimation via Markov chain Monte Carlo (MCMC) Metropolis-within-Gibbs sampling, likelihood-based parametric bootstrap goodness-of-fit (GOF) tests, profile log-likelihood diagnostics, and discrete survival and probability calculations. Methods are based on Ahmad and Mansour (2026) <doi:10.1155/jom/3657078>, Balakrishnan and Dembinska (2008) <doi:10.1016/j.jspi.2007.02.006>, Joe and Zhu (2005) <doi:10.1002/bimj.200410102>, and Balakrishnan and Aggarwala (2000, ISBN:978-1-4612-1334-5).

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: stats, graphics
Suggests: testthat (≥ 3.0.0)
Published: 2026-08-21
DOI: 10.32614/CRAN.package.TieFreeCensor
Author: Shikhar Tyagi ORCID iD [aut, cre], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: TieFreeCensor results

Documentation:

Reference manual: TieFreeCensor.html , TieFreeCensor.pdf

Downloads:

Package source: TieFreeCensor_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: TieFreeCensor_0.1.0.zip, r-oldrel: TieFreeCensor_0.1.0.zip
macOS binaries: r-release (arm64): TieFreeCensor_0.1.0.tgz, r-oldrel (arm64): TieFreeCensor_0.1.0.tgz, r-release (x86_64): TieFreeCensor_0.1.0.tgz, r-oldrel (x86_64): TieFreeCensor_0.1.0.tgz

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