Plot for Robust or Taguchi Designs

DESCRIPTION:

Creates plots for robust or Taguchi designs.

USAGE:

plot.robust.design(x, y = NULL, fun = mean, data.pts=T, ...) 

REQUIRED ARGUMENTS:

x
an object of class "robust.design".

OPTIONAL ARGUMENTS:

y
the response(s). If a response is not given, all non-factor components of x will be the response(s).
fun
the function to be applied to the data in each factor level.
data.pts
logical flag for whether data points are plotted.
print.values
a logical flag for whether mean values will be added to plot.
...
arguments passed to plot.

SIDE EFFECTS:

A version of a main effects plot is produced on the current graphics device.

DETAILS:

Experiments using robust design methods are usually intended to detect factors that influence the variance and/or the mean. The vertical lines for each factor level indicate the smallest and largest observations; the lines joining the levels show the change in the mean. The plot is designed to draw attention to the range of observations within each level of a factor (as a surrogate for the variance) in addition to the change in mean.

SEE ALSO:

, , , .

EXAMPLES:

plot(mold.df)