Assessment for statistically-based PPQ sampling plan, including calculating the passing probability, optimizing the baseline and high performance cutoff points, visualizing the PPQ plan and power dynamically. The analytical idea is based on the simulation methods from the textbook "Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical Methods for CMC Applications. In Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry (pp. 227-250). Springer, Cham."
| Version: | 0.1.0 |
| Imports: | tolerance, ggplot2, plotly |
| Suggests: | knitr, rmarkdown |
| Published: | 2018-06-15 |
| Author: | Yalin Zhu |
| Maintainer: | Yalin Zhu <yalin.zhu at merck.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Copyright: | Copyright 2018, Center for Mathematical Sciences, Merck & Co., Inc. |
| NeedsCompilation: | no |
| CRAN checks: | PPQplan results |
| Reference manual: | PPQplan.pdf |
| Vignettes: |
Vignette Title |
| Package source: | PPQplan_0.1.0.tar.gz |
| Windows binaries: | r-devel: PPQplan_0.1.0.zip, r-release: PPQplan_0.1.0.zip, r-oldrel: PPQplan_0.1.0.zip |
| OS X binaries: | r-release: PPQplan_0.1.0.tgz, r-oldrel: PPQplan_0.1.0.tgz |
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