View source: R/3.3_Factorial_designs_Functions.R
normalPlot | R Documentation |
Creates a normal probability plot for the effects in a facDesign.c
object.
normalPlot(
dfac,
response = NULL,
main,
ylim,
xlim,
xlab,
ylab,
pch,
col,
border = "red"
)
dfac |
An object of class |
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 |
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 |
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. |
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').
The function normalPlot
returns an invisible list containing:
effects |
a list of effects for each response in the |
plot |
The generated normal plot. |
facDesign
, paretoPlot
, interactionPlot
# 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)
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