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) , Balakrishnan and Dembinska (2008) , Joe and Zhu (2005) , and Balakrishnan and Aggarwala (2000, ISBN:978-1-4612-1334-5).