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PPQplan
View on CRAN: Click
here
Download and install PPQplan package within the R console
Install from CRAN:
install.packages("PPQplan")
Install from Github:
library("remotes")
install_github("cran/PPQplan") Install by package version:
library("remotes")
install_version("PPQplan", "1.1.0") Attach the package and use:
library("PPQplan")
Maintained by
Yalin Zhu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-15
Latest Update: 2020-10-08
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.
How to cite:
Yalin Zhu (2018). PPQplan: Process Performance Qualification (PPQ) Plans in Chemistry, Manufacturing and Controls (CMC) Statistical Analysis. R package version 1.1.0, https://cran.r-project.org/web/packages/PPQplan. Accessed 26 Aug. 2026.
Previous versions and publish date:
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Other R packages that PPQplan depends,
imports, suggests or enhances
Complete documentation for PPQplan
Functions, R codes and Examples using
the PPQplan R package
Some associated functions: PPQ_ctplot . PPQ_ggplot . PPQ_occurve . PPQ_pp . heatmap_ly . k_factor . pi_ctplot . pi_occurve . pi_pp . pp . rl_pp . ti_ctplot . ti_occurve . ti_pp .
Some associated R codes: PPQ_ctplot.R . PPQ_ggplot.R . PPQ_occurve.R . PPQ_pp.R . global_var.R . heatmap_ly.R . k_factor.R . pi_ctplot.R . pi_occurve.R . pi_pp.R . pp.R . rl_pp.R . ti_ctplot.R . ti_occurve.R . ti_pp.R . Full PPQplan package functions and examples
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