Package: PPQplan
Type: Package
Title: Process Performance Qualification (PPQ) Plans in Chemistry,
        Manufacturing and Controls (CMC) Statistical Analysis
Version: 1.1.0
Authors@R: c(
    person("Yalin", "Zhu", , "yalin.zhu@merck.com", role = c("aut", "cre"), 
      comment = c(ORCID = "0000-0003-3830-8660")), 
    person("Merck & Co., Inc.", role = c("cph"))
    )
Maintainer: Yalin Zhu <yalin.zhu@merck.com>
Depends: R (>= 3.2.0)
Imports: ggplot2, plotly
Description: 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.
License: GPL-3
Suggests: knitr, rmarkdown, devtools
VignetteBuilder: knitr
NeedsCompilation: no
RoxygenNote: 7.1.0
Encoding: UTF-8
URL: https://allenzhuaz.github.io/PPQplan/,
        https://github.com/allenzhuaz/PPQplan
BugReports: https://github.com/allenzhuaz/PPQplan/issues
LazyData: true
Language: en-US
Packaged: 2020-10-08 02:01:06 UTC; zhuyal
Author: Yalin Zhu [aut, cre] (<https://orcid.org/0000-0003-3830-8660>),
  Merck & Co., Inc. [cph]
Repository: CRAN
Date/Publication: 2020-10-08 04:30:06 UTC
Built: R 4.4.3; ; 2026-04-22 04:13:03 UTC; windows
