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MultiStepSSAD: Multiple-Steps Step-Stress Accelerated Degradation Modeling

Implements statistical methods for multiple-steps step-stress accelerated degradation testing (SSADT) based on Wiener processes and Gamma processes as described by Pan and Balakrishnan (2010) <doi:10.1080/03610918.2010.496060>. Features maximum likelihood estimation (MLE), Bayesian Markov chain Monte Carlo (MCMC) sampling, Geweke convergence diagnostics, and reliability predictions under normal operating stress conditions.

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: stats, graphics, grDevices, utils
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-08-07
DOI: 10.32614/CRAN.package.MultiStepSSAD
Author: Shikhar Tyagi ORCID iD [aut, cre], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: MultiStepSSAD results

Documentation:

Reference manual: MultiStepSSAD.html , MultiStepSSAD.pdf
Vignettes: Multiple-Steps Step-Stress Accelerated Degradation Modeling (source, R code)

Downloads:

Package source: MultiStepSSAD_0.1.0.tar.gz
Windows binaries: r-devel: MultiStepSSAD_0.1.0.zip, r-release: MultiStepSSAD_0.1.0.zip, r-oldrel: MultiStepSSAD_0.1.0.zip
macOS binaries: r-release (arm64): MultiStepSSAD_0.1.0.tgz, r-oldrel (arm64): MultiStepSSAD_0.1.0.tgz, r-release (x86_64): MultiStepSSAD_0.1.0.tgz, r-oldrel (x86_64): MultiStepSSAD_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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