Package: DropCens 0.1.0

DropCens: Distributionally Robust Progressive Type-II Censoring Inference

Implements distributionally robust optimization algorithms for progressive Type-II censored Weibull lifetime data under Wasserstein ambiguity balls. Provides primal-dual convex optimization solvers and robust inference bounds.

Authors:Okechukwu J. Obulezi [aut, cre]

DropCens_0.1.0.tar.gz
DropCens_0.1.0.zip(r-4.7-any)DropCens_0.1.0.zip(r-4.6-any)DropCens_0.1.0.zip(r-4.5-any)
DropCens_0.1.0.tgz(r-4.6-any)DropCens_0.1.0.tgz(r-4.5-any)
DropCens_0.1.0.tar.gz(r-4.7-any)DropCens_0.1.0.tar.gz(r-4.6-any)
DropCens_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
DropCens/json (API)

# Install 'DropCens' in R:
install.packages('DropCens', repos = c('https://obulezi-oj.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 210 downloads 2 exports 0 dependencies

Last updated from:bbe5b44a47. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK87
source / vignettesOK122
linux-releaseOK83
macos-releaseOK74
macos-oldrelOK144
windows-develOK56
windows-releaseOK54
windows-oldrelOK50
wasm-releaseOK66

Exports:dro_bayesian_boundsfit_dro_pc

Dependencies: