Use of one of these functions in a model is how you specify the portion of the model that is to be regarded as a response-surface component.
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The numerical predictors for the response surface, separated by commas.
Alternative way to specify two-way interactions. Use
FO() in the model formula in
to specify a first-order response surface (i.e., a linear function)
in its arguments. Use
TWI() to generate two-way interactions, and
PQ() to generate
pure quadratic terms (squares of the
FO() terms). A call to
SO() creates all terms in
PQ() (in that order) for those
variables. However, specifying
SO() in a model formula in
rsm will be replaced
by the explicit sum of model terms, so that the
anova table shows separate sums of squares.
Other variables (such as blocks or factors) may be included in the model
but should never be included in the arguments to
PE is used for fitting pure-error models. It should not be used in
response-surface models. This function exists primarily for use
loftest, but could be useful in other linear-model
contexts for fitting a model that interpolates the means at each distinct
combination of argument values.
formula argument in
TWI can simplify specifying models where only certain interactions are included. For example, TWI(formula = ~x1:(x2+x3)) is equivalent to TWI(x1,x2) + TWI(x1,x3). The formula is expanded using
terms, and then only the second-order terms are retained. If this results in only one term, an error condition is raised. This is necessary to prevent
rsm from getting confused in identifying second-order terms.
SO return a matrix whose
columns are the required predictors.
PE returns a
factor whose levels are all the distinct combinations of
arguments provided to the function.
Russell V. Lenth
Lenth RV (2009) “Response-Surface Methods in R, Using rsm”, Journal of Statistical Software, 32(7), 1–17. http://www.jstatsoft.org/v32/i07/.
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