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).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | TieFreeCensor_0.1.0.tar.gz |
99.7 KiB |
0.1.0 |
rolling linux/noble R-4.5 | TieFreeCensor_0.1.0.tar.gz |
99.7 KiB |
0.1.0 |
rolling source/ R- | TieFreeCensor_0.1.0.tar.gz |
19.2 KiB |
0.1.0 |
latest linux/jammy R-4.5 | TieFreeCensor_0.1.0.tar.gz |
99.7 KiB |
0.1.0 |
latest linux/noble R-4.5 | TieFreeCensor_0.1.0.tar.gz |
99.7 KiB |
0.1.0 |
latest source/ R- | TieFreeCensor_0.1.0.tar.gz |
19.2 KiB |
0.1.0 |
2026-04-23 source/ R- | TieFreeCensor_0.1.0.tar.gz |
0 B |