Overview | Example inspection data | Prepare the data | Find a baseline acceptance sampling plan | Apply DRAS monitoring | Summarise monitoring results | Supplier-level summary | Write an audit report | Interpretation
Package: drasR 0.1.0
Muhammad Zahir Khan
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.
Authors:
drasR_0.1.0.tar.gz
drasR_0.1.0.zip(r-4.7-any)drasR_0.1.0.zip(r-4.6-any)
drasR_0.1.0.tar.gz(r-4.7-any)drasR_0.1.0.tar.gz(r-4.6-any)
drasR_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
drasR/json (API)
| # Install 'drasR' in R: |
| install.packages('drasR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/zerish12/drasr/issues
Datasets:
- example_lot_data - Example Lot Inspection Data
Last updated from:b55edce6a8. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 116 | ||
| source / vignettes | OK | 148 | ||
| linux-release | OK | 109 | ||
| windows-devel | OK | 96 | ||
| windows-release | OK | 100 | ||
| wasm-release | OK | 79 |
Exports:apply_fixed_planconsumer_riskdecision_fragilitydras_ewmadras_monitorevaluate_samplingfind_planpareto_frontierplot_dras_frontierprepare_lot_dataprob_acceptproducer_riskrun_dras_experimentselect_dras_policysimulate_defect_processsimulate_lotssummarise_dras_monitortune_dras_policywrite_dras_report
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Apply a Fixed Acceptance Sampling Plan | apply_fixed_plan |
| Consumer Risk | consumer_risk |
| Acceptance Decision Fragility | decision_fragility |
| Apply EWMA Drift-Aware Acceptance Sampling | dras_ewma |
| Monitor Real Lot Inspection Data Using DRAS | dras_monitor |
| Evaluate Lot-Disposition Results | evaluate_sampling |
| Example Lot Inspection Data | example_lot_data |
| Find a Single Acceptance Sampling Plan | find_plan |
| Compute a Safety-Cost Pareto Frontier | pareto_frontier |
| Plot the DRAS Safety-Cost Frontier | plot_dras_frontier |
| Prepare Real Lot-Level Inspection Data | prepare_lot_data |
| Probability of Accepting a Lot | prob_accept |
| Producer Risk | producer_risk |
| Run a DRAS Monte Carlo Experiment | run_dras_experiment |
| Select Low-Cost, Balanced, and High-Safety DRAS Policies | select_dras_policy |
| Simulate a Defect Process | simulate_defect_process |
| Simulate Lot Inspection Data | simulate_lots |
| Summarise DRAS Monitoring Results | summarise_dras_monitor |
| Tune DRAS Policies | tune_dras_policy |
| Write a DRAS Audit Report | write_dras_report |