The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Implements Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo (MCMC) sampling algorithms for progressive censoring models, with support for dynamic reinforcement learning environment simulation and accelerated computational routines written in C++.
| Version: | 0.1.1 |
| Imports: | Rcpp, stats |
| LinkingTo: | Rcpp |
| Published: | 2026-08-25 |
| DOI: | 10.32614/CRAN.package.DRLAP2 |
| Author: | Okechukwu J. Obulezi [aut, cre] |
| Maintainer: | Okechukwu J. Obulezi <oj.obulezi at unizik.edu.ng> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| CRAN checks: | DRLAP2 results |
| Reference manual: | DRLAP2.html , DRLAP2.pdf |
| Package source: | DRLAP2_0.1.1.tar.gz |
| Windows binaries: | r-devel: DRLAP2_0.1.1.zip, r-release: DRLAP2_0.1.1.zip, r-oldrel: DRLAP2_0.1.1.zip |
| macOS binaries: | r-release (arm64): DRLAP2_0.1.1.tgz, r-oldrel (arm64): DRLAP2_0.1.1.tgz, r-release (x86_64): DRLAP2_0.1.1.tgz, r-oldrel (x86_64): DRLAP2_0.1.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=DRLAP2 to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.