PINNProgCens: Physics-Informed Neural Networks for Progressive Censoring

Implementation of Physics-Informed Neural Networks ('PINN') for lifetime estimation under progressive Type-II censoring schemes. Combines parametric baseline hazards with physical differential degradation models.

Version: 0.1.0
Imports: deSolve, stats
Published: 2026-08-09
DOI: 10.32614/CRAN.package.PINNProgCens (may not be active yet)
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi at unizik.edu.ng>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: PINNProgCens results

Documentation:

Reference manual: PINNProgCens.html , PINNProgCens.pdf

Downloads:

Package source: PINNProgCens_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: PINNProgCens_0.1.0.zip
macOS binaries: r-release (arm64): PINNProgCens_0.1.0.tgz, r-oldrel (arm64): PINNProgCens_0.1.0.tgz, r-release (x86_64): PINNProgCens_0.1.0.tgz, r-oldrel (x86_64): PINNProgCens_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PINNProgCens to link to this page.