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pcsclr  

Progressive Censoring Schemes with Competitive Latent-Risk
View on CRAN: Click here


Download and install pcsclr package within the R console
Install from CRAN:
install.packages("pcsclr")

Install from Github:
library("remotes")
install_github("cran/pcsclr")

Install by package version:
library("remotes")
install_version("pcsclr", "0.1.1")



Attach the package and use:
library("pcsclr")
Maintained by
Okechukwu J. Obulezi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-30
Latest Update: 2026-07-30
Description:
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.
How to cite:
Okechukwu J. Obulezi (2026). pcsclr: Progressive Censoring Schemes with Competitive Latent-Risk. R package version 0.1.1, https://cran.r-project.org/web/packages/pcsclr. Accessed 27 Oct. 2026.
Previous versions and publish date:
No previous versions
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Complete documentation for pcsclr
Functions, R codes and Examples using the pcsclr R package
Full pcsclr package functions and examples
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