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AdaptHyCensor

0.1.0

Generalized Inference and Data Generation for Adaptive Progressive Hybrid Censoring Schemes

0packages depend
45downloads / year
52.3%test coverage
11/11checks pass

Overview

About
Maintained by Shikhar TyagiFirst published 2026-08-041 releasesCRAN page ↗

Comprehensive computational tools for data generation, statistical inference, and visual diagnostics under Adaptive Type-I and Adaptive Type-II Progressive Hybrid Censoring Schemes. Users can supply custom probability density functions (PDF), cumulative distribution functions (CDF), survival functions, parameter ranges, and progressive schemes for any univariate lifetime distribution. Parameter estimation methods include Maximum Likelihood Estimation (MLE) using multiple optimization algorithms (Newton-Raphson (NR), Broyden-Fletcher-Goldfarb-Shanno (BFGS), BFGS in R (BFGSR), Berndt-Hall-Hall-Hausman (BHHH), Simulated Annealing (SANN), Conjugate Gradients (CG), and Nelder-Mead (NM)), Bayesian estimation via Gibbs and Metropolis-Hastings (M-H) MCMC sampling, Importance Sampling (IS), and Lindley's approximation. Diagnostic tools provide histograms, dot plots, and autocorrelation function (ACF) plots for model validation. Methods are based on Balakrishnan, Cramer, and Kundu (2023, ISBN:978-0-12-398387-9), Ng, Kundu, and Chan (2009, IEEE Transactions on Reliability, 58, 634-642), Lin and Huang (2012, Journal of Statistical Computation and Simulation, 82, 1005-1018), Lindley (1980, Journal of the Royal Statistical Society, Series B, 42, 223-237), and Berndt, Hall, Hall, and Hausman (1974, Annals of Economic and Social Measurement, 3, 653-665).

Install

Health

CRAN checks
11OK
Slowest check: 1.5 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.05
52.3%
Coverage · measured lines
100%
Documentation · exports
2
Dependencies · direct
Check history
  • OK2026-08-05
    7 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
14%

Downloads

45
CRAN downloads in the past year
Rank #24,703 · ~0/day · ~4/mo
AdaptHyCensor
Daily download trend is not available in this view yet.

Dependencies

Declared dependencies
1 external dependency (excludes base and recommended)
Depends (1)
R >= 4.0.0
Imports (2)
statsgraphics
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (4)
Maintainer (1)
Author, Maintainer
Authors (4)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • 0.1.0Latest
    2026-08-04 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-08-04
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.0.0
Download size
not tracked yet
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("AdaptHyCensor")
Tyagi, S., Pandey, A., Singh, B., & Tripathi, V. (2026). AdaptHyCensor: Generalized Inference and Data Generation for Adaptive Progressive Hybrid Censoring Schemes (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.AdaptHyCensor

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for AdaptHyCensor version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-08-08. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-08, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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