heatmap_ly: A General Heatmap for Dynamically Assessing Power of the...

In PPQplan: Process Performance Qualification (PPQ) Plans in Chemistry, Manufacturing and Controls (CMC) Statistical Analysis

Description

The function for dynamically plotting (ggplot) the heatmap to evaluate the sampling plan based on a general lower and/or upper specification limits.

Usage

heatmap_ly(attr.name, attr.unit, Llim, Ulim, mu, sigma, n, test.point, dynamic)

Arguments

attr.name	(optional) user-defined attribute name for sampling plan assessment
attr.unit	(optional) user-defined attribute unit
Llim	lower specification limit
Ulim	upper specification limit
mu	hypothetical mean of the attribute
sigma	hypothetical standard deviation of the attribute
n	sample size (number of locations) per batch
test.point	(optional) actual process data points for testing whether the processes pass PPQ
dynamic	logical; if TRUE, then convert the plain heatmap to dynamic graph using plotly.

Value

A Plain or Dynamic Heatmap for Sampling Plan Assessment.

Author(s)

Yalin Zhu

References

Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry. Springer.

See Also

pp and PPQ.occurve.

Examples

## Not run: 
heatmap_ly(attr.name = "Thickness", attr.unit = "%",Llim = -0.2, Ulim = 0.2,
mu = seq(-0.2, 0.2, 0.001), sigma = seq(0,0.2, 0.001),
test.point=data.frame(c(0.1,-0.05),c(0.15,0.05)), n=2, dynamic = T)

## End(Not run)

Example output

PPQplan documentation built on Jan. 13, 2021, 9:49 p.m.