convert.to.rsm(fac.df, factors, numeric.levels,
n.cp = min(n.factors + 1,4), alpha = nrow(fac.df)^(1/4),
logx = F, keep.all = TRUE)
fac.design frame, or a design with only two level factors.
fac.df. These factors will be
used to construct the
rsm.design. By default, all two level factors are used.
factors. If this is omitted, default values for the two levels are 1
and 2.
rsm.design for details.
TRUE if all variables in
fac.df are in the
returned
rsm.design;
FALSE if only the variables given by
factor.
rsm.design object derived from
fac.df, with additional rows for
star and center points. The returned object is a central composite
design. The factors of
fac.df are converted to
rsm.factor
s, that is, continuous variables with center points and
star points added. If
keep.all=TRUE the non-factor variables are
augmented with NAs.
This function helps when an initial screening experiment is to be augmented with additional points to allow fitting a quadratic response surface.
bufferr.df <- convert.to.rsm(buffer.df, numeric = c(-1,1),
keep = F)
temp1 <- rsm.design(5, names(buffer.df)[1:5], fraction = 1/2)
all.equal(bufferr.df, temp1)
convert.to.rsm(design.digest('ff0308'), numeric =
list(A = c(-1,1), B = c(10,20), C = c(0,1)))