DanielPlot {BsMD}R Documentation

Normal Plot of Effects

Description

Normal plot of effects from a two level factorial experiment.

Usage

DanielPlot(fit, code = FALSE, faclab = NULL, block = FALSE,
    datax = TRUE, half = FALSE, pch = "*", cex.fac = par("cex.lab"), 
    cex.lab = par("cex.lab"), cex.pch = par("cex.axis"), ...)

Arguments

fit object of class lm. Fitted model from lm or aov.
code logical. If TRUE labels "A","B", etc are used instead of the names of the coefficients (factors).
faclab list. If NULL points are labelled accordingly to code, otherwise faclab should be a list with idx (integer vector) and lab (character vector) components. See Details.
block logical. If TRUE, the first factor is labelled as "BK" (block).
datax logical. If TRUE, the x-axis is used for the factor effects the the y-axis for the normal scores. The opposite otherwise.
half logical. If TRUE, half-normal plot of effects is display.
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 plot.

Details

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 x-axis by default. If half=TRUE the half-normal plots of effects is plotted as the normal quantiles of 0.5*(rank(abs(effects))-0.5)/length(effects)+1 versus abs(effects).

Value

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.

Author(s)

Ernesto Barrios.

References

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.

See Also

qqnorm, LenthPlot

Examples

### 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 = "Half-Normal 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")

[Package BsMD version 0.6-5.2 Index]