pareto(x, method=<<see below>>, sig=.05, xmax=<<see below>>,
prt.values=T, shade=F, ...)
fac.aov object, typically created by
fac.aov.
all lines are drawn;
"pse" if
df.residual = 0, otherwise, if
"mse" is
available, both
"mse" and
"pse" are used.
xlim.
If
fac.aov or
update.fac.aov are used to create an unsaturated
model, then the Pareto plot will show the
seffects (from the
saturated model) rather than the
feffects. The significance
line for the
pse method will also be based on the
seffects.
Haaland, P. D. (1989),
Experimental Design in Biotechnology,
New York: Marcel Dekker.
Haaland, P. D. and M. A. O'Connell (1994), Inference for effect
saturated fractional factorials, to appear in Technometrics.
buffer.fac <- fac.aov(buffer.df) pareto(buffer.fac) # use all defaults pareto(buffer.fac, sig=.1) # use .1 significance level to plot lines pareto(buffer.fac, method="none") # do not plot significance lines pareto(buffer.fac, "all") # plot all possible significance lines pareto(buffer.fac, "ase") # plot only "ase" significance line # show what happens with an unsaturated model buffer.fac1 <- update(buffer.fac,~pH*thimer+pH*gent) pareto(buffer.fac1) buffer.fac2 <- fac.aov(rate~pH*thimer+pH*gent,buffer.df) pareto(buffer.fac2)