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cff-version: 1.2.0
message: 'To cite package "drasR" in publications use:'
type: software
license: MIT
title: 'drasR: Drift-Aware Risk-Guaranteed Acceptance Sampling'
version: 0.1.0
abstract: 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) <https://doi.org/10.1080/00401706.1959.10489860>.
  The methods are intended for simulation studies, supplier quality monitoring, and
  audit-oriented inspection decision support.
authors:
- family-names: Khan
  given-names: Muhammad Zahir
  email: zahirstat007@gmail.com
repository: https://cran.r-universe.dev
repository-code: https://github.com/zerish12/drasR
commit: b55edce6a834c01b3bced3b2c112bdda97a362e6
url: https://github.com/zerish12/drasR
date-released: '2026-11-06'
contact:
- family-names: Khan
  given-names: Muhammad Zahir
  email: zahirstat007@gmail.com