drasR: Drift-Aware Risk-Guaranteed Acceptance Sampling

Implements drift-aware risk-guaranteed acceptance sampling methods for adaptive lot disposition. The package provides tools for classical acceptance sampling, producer-risk and consumer-risk assessment, exponentially weighted moving average drift monitoring, adaptive tightening policies, decision fragility analysis, and safety-cost Pareto frontier construction. Classical binomial acceptance-plan design is described in the NIST/SEMATECH e-Handbook of Statistical Methods <https://www.itl.nist.gov/div898/handbook/pmc/section2/pmc232.htm>. Exponentially weighted moving averages follow Roberts (1959) <doi:10.1080/00401706.1959.10489860>. The methods are intended for simulation studies, supplier quality monitoring, and audit-oriented inspection decision support.

Version:	0.1.0
Depends:	R (≥ 4.1.0)
Imports:	stats, graphics, utils
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-11-06
DOI:	10.32614/CRAN.package.drasR
Author:	Muhammad Zahir Khan [aut, cre]
Maintainer:	Muhammad Zahir Khan <zahirstat007 at gmail.com>
BugReports:	https://github.com/zerish12/drasR/issues
License:	MIT + file LICENSE
URL:	https://github.com/zerish12/drasR
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	drasR results

Documentation:

Reference manual:	drasR.html , drasR.pdf
Vignettes:	Using drasR with Real Inspection Data (source, R code)

Downloads:

Package source:	drasR_0.1.0.tar.gz
Windows binaries:	r-devel: drasR_0.1.0.zip, r-release: not available, r-oldrel: drasR_0.1.0.zip
macOS binaries:	r-release (arm64): drasR_0.1.0.tgz, r-oldrel (arm64): drasR_0.1.0.tgz, r-release (x86_64): drasR_0.1.0.tgz, r-oldrel (x86_64): drasR_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=drasR to link to this page.