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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | pcsclr_0.1.1.tar.gz |
55.4 KiB |
0.1.1 |
rolling linux/noble R-4.5 | pcsclr_0.1.1.tar.gz |
56.3 KiB |
0.1.1 |
rolling source/ R- | pcsclr_0.1.1.tar.gz |
7.6 KiB |
0.1.1 |
latest linux/jammy R-4.5 | pcsclr_0.1.1.tar.gz |
55.4 KiB |
0.1.1 |
latest linux/noble R-4.5 | pcsclr_0.1.1.tar.gz |
56.3 KiB |
0.1.1 |
latest source/ R- | pcsclr_0.1.1.tar.gz |
7.6 KiB |
0.1.1 |
2026-04-23 source/ R- | pcsclr_0.1.1.tar.gz |
0 B |