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CRAN: Package pcsclr

pcsclr: Progressive Censoring Schemes with Competitive Latent-Risk

Implements simulation, numerical maximum likelihood estimation via fourth-order Runge-Kutta path optimization, and high-speed Bayesian Markov Chain Monte Carlo (MCMC) samplers for Weibull lifetimes under progressive censoring setups with competitive latent risks. Both point estimation and interval estimation are provided for the model parameters.

Version: 0.1.1
Imports: graphics, Rcpp (≥ 1.0.0), stats
LinkingTo: Rcpp, RcppArmadillo
Published: 2026-07-30
DOI: 10.32614/CRAN.package.pcsclr
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi at unizik.edu.ng>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
CRAN checks: pcsclr results

Documentation:

Reference manual: pcsclr.html , pcsclr.pdf

Downloads:

Package source: pcsclr_0.1.1.tar.gz
Windows binaries: r-devel: pcsclr_0.1.1.zip, r-release: pcsclr_0.1.1.zip, r-oldrel: pcsclr_0.1.1.zip
macOS binaries: r-release (arm64): pcsclr_0.1.1.tgz, r-oldrel (arm64): pcsclr_0.1.1.tgz, r-release (x86_64): pcsclr_0.1.1.tgz, r-oldrel (x86_64): pcsclr_0.1.1.tgz

Linking:

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