normalPlot: normalPlot: Normal plot

Description

Creates a normal probability plot for the effects in a facDesign.c object.

Usage

normalPlot(
  dfac,
  response = NULL,
  main,
  ylim,
  xlim,
  xlab,
  ylab,
  pch,
  col,
  border = "red"
)

Value

The function normalPlot returns an invisible list containing:

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

Arguments

dfac: An object of class facDesign.c.
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 respons` is set to NULL.
main: Character string specifying the main title of the plot.
ylim: Graphical parameter. The y limits of the plot.
xlim: Graphical parameter. The x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a `reversed axis`.
xlab: Character string specifying the label for the x-axis.
ylab: Character string specifying the label for the y-axis.
pch: Graphical parameter. Vector containing numerical values or single characters giving plotting points for the different factors. Accepts values from 0 to 25, each corresponding to a specific shape in ggplot2 (e.g., 0: square, 1: circle, 2: triangle point up, 3: plus, 4: cross).
col: Graphical parameter. Single numerical value or character string giving the color for the points (e.g., 1: black, 2: red, 3: green).
border: Graphical parameter. Single numerical value or character string giving the color of the border line.

Details

If the given facDesign.c object fdo contains replicates this function will deliver a normal plot i.e.: effects divided by the standard deviation (t-value) will be plotted against an appropriate probability scaling (see: `ppoints`). If the given facDesign.c object fdo contains no replications the standard error can not be calculated. In that case the function will deliver an effect plot. i.e.: the effects will be plotted against an appropriate probability scaling. (see: `ppoints`).

Examples

Run this code

# Example 1: Create a normal probability plot for a full factorial design
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)

normalPlot(dfac)

# Example 2: Create a normal probability plot with custom colors and symbols
normalPlot(dfac, col = "blue", pch = 4)