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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 |
| 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 |
| Reference manual: | PINNProgCens.html , PINNProgCens.pdf |
| Package source: | PINNProgCens_0.1.0.tar.gz |
| Windows binaries: | r-devel: PINNProgCens_0.1.0.zip, r-release: PINNProgCens_0.1.0.zip, 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 |
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