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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "PINNProgCens" in publications use:'
type: software
license: MIT
title: 'PINNProgCens: Physics-Informed Neural Networks for Progressive Censoring'
version: 0.1.0
doi: 10.32614/CRAN.package.PINNProgCens
abstract: 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.
authors:
- family-names: Obulezi
  given-names: Okechukwu J.
  email: oj.obulezi@unizik.edu.ng
repository: https://obulezi-oj.r-universe.dev
commit: bbd5d7cf4e31409259c8e1547381fbe123817271
date-released: '2026-08-09'
contact:
- family-names: Obulezi
  given-names: Okechukwu J.
  email: oj.obulezi@unizik.edu.ng