Normal plot of effects from a two level factorial experiment.
1 2 3 
fit 
object of class 
code 
logical. If 
faclab 
list. If 
block 
logical. If 
datax 
logical. If 
half 
logical. If 
pch 
numeric or character. Points character. 
cex.fac 
numeric. Factors' labels character size. 
cex.lab 
numeric. Labels character size. 
cex.pch 
numeric. Points character size. 
... 
graphical parameters passed to 
The two levels design are assumed 1 and 1. Factor effects assumed 2*coef(obj)
((Intercept) removed) are displayed in a qqnorm
plot with the effects in
the xaxis by default. If half=TRUE
the halfnormal plots of effects is
plotted as the normal quantiles of 0.5*(rank(abs(effects))0.5)/length(effects)+1
versus abs(effects)
.
The function returns invisible data frame with columns: x
, y
and no
, for the coordinates and the enumeration of plotted points.
Names of the factor effects (coefficients) are the row names of the data frame.
Ernesto Barrios.
C. Daniel (1976). Application of Statistics to Industrial Experimentation. Wiley.
Box G. E. P, Hunter, W. C. and Hunter, J. S. (1978). Statistics for Experimenters. Wiley.
qqnorm
, LenthPlot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  ### Injection Molding Experiment. Box et al. 1978.
library(BsMD)
# Data
data(BM86.data,package="BsMD") # Design matrix and response
print(BM86.data) # from Box and Meyer (1986)
# Model Fitting. Box and Meyer (1986) example 3.
injectionMolding.lm < lm(y3 ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 +
X10 + X11 + X12 + X13 + X14 + X15, data = BM86.data)
print(coef(injectionMolding.lm)) # Model coefficients
# Daniel Plots
par(mfrow=c(1,3),oma=c(0,0,1,0),pty="s")
DanielPlot(injectionMolding.lm, half = TRUE, main = "HalfNormal Plot")
DanielPlot(injectionMolding.lm, main = "Normal Plot of Effects")
DanielPlot(injectionMolding.lm,
faclab = list(idx = c(12,4,13), lab = c(" H"," VG"," B")),
main = "Active Contrasts")

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