paretoPlot: paretoPlot

In r6qualitytools: R6-Based Statistical Methods for Quality Science

paretoPlot

Description

Display standardized effects and interactions of a facDesign.c object in a pareto plot.

Usage

paretoPlot(
  dfac,
  abs = TRUE,
  decreasing = TRUE,
  alpha = 0.05,
  response = NULL,
  ylim,
  xlab,
  ylab,
  main,
  p.col,
  legend_left = TRUE
)

Arguments

dfac	An object of class facDesign.
abs	Logical. If TRUE, absolute effects and interactions are displayed. Default is TRUE.
decreasing	Logical. If TRUE, effects and interactions are sorted decreasing. Default is TRUE.
alpha	The significance level used to calculate the critical value
response	Response variable. If the response data frame of fdo consists of more then one responses, this variable can be used to choose just one column of the response data frame. response needs to be an object of class character with length of '1'. It needs to be the same character as the name of the response in the response data frame that should be plotted. By default response is set to NULL.
ylim	Numeric vector of length 2: limits for the y-axis. If missing, the limits are set automatically.
xlab	Character string: label for the x-axis.
ylab	Character string: label for the y-axis.
main	Character string: title of the plot.
p.col	Character string specifying the color palette to use for the plot. Must be one of the following values from the RColorBrewer package: `Set1` `Set2` `Set3` `Pastel1` `Pastel2` `Paired` `Dark2` `Accent`
legend_left	Logical value indicating whether to place the legend on the left side of the plot. Default is TRUE.

Details

paretoPlot displays a pareto plot of effects and interactions for an object of class facDesign (i.e. 2^k full or 2^k-p fractional factorial design). For a given significance level alpha, a critical value is calculated and added to the plot. Standardization is achieved by dividing estimates with their standard error. For unreplicated fractional factorial designs a Lenth Plot is generated.

Value

The function paretoPlot returns an invisible list containing:

effects	a list of effects for each response in the facDesign.c object
plot	The generated PP plot.

See Also

fracDesign, facDesign

Examples

# Create the facDesign object
dfac <- facDesign(k = 3, centerCube = 4)
dfac$names(c('Factor 1', 'Factor 2', 'Factor 3'))

# Assign performance to the factorial design
rend <- c(simProc(120,140,1), simProc(80,140,1), simProc(120,140,2),
          simProc(120,120,1), simProc(90,130,1.5), simProc(90,130,1.5),
          simProc(80,120,2), simProc(90,130,1.5), simProc(90,130,1.5),
          simProc(120,120,2), simProc(80,140,2), simProc(80,120,1))
dfac$.response(rend)

paretoPlot(dfac)
paretoPlot(dfac, decreasing = TRUE, abs = FALSE, p.col = "Pastel1")

r6qualitytools documentation built on Oct. 4, 2024, 1:09 a.m.