stepEvolution {DiceEval}  R Documentation 
Graphical representation of the selected terms using stepwise procedure for different values of the penalty parameter.
stepEvolution(X,Y,formula,P=1:7,K=10,test=NULL,graphic=TRUE)
X 
a data.frame containing the design of experiments 
Y 
a vector containing the response variable 
formula 
a formula for the initial model 
P 
a vector containing different values of the penalty parameter for which a stepwise selected model is fitted 
K 
the number of folds for the crossvalidation procedure 
test 
an additional data set on which the prediction criteria are evaluated (default corresponds to no test data set) 
graphic 
if 
a list with the different criteria for different values of the penalty parameter. This list contains:
penalty 
the values for the penalty parameter 
m 
size 
R2 
the value of the 
According to the value of the test
argument, other criteria are calculated:
a.  If a test set is available, R2test contains the value of the R2
criterion on the test set 
b.  If no test set is available, the Q2 and the RMSE computed by
crossvalidation are done.

Plots are also available.
A tabular represents the selected terms for each value in P
.
The evolution of the R2
criterion, the evolution of the size m
of the selected
model and criteria on the test set or by Kfolds crossvalidation are represented.
These graphical tools can be used to select the best value for the penalty parameter.
D. Dupuy
step
procedure for linear models.
## Not run:
data(dataIRSN5D)
design < dataIRSN5D[,1:5]
Y < dataIRSN5D[,6]
out < stepEvolution(design,Y,formulaLm(design,Y),P=c(1,2,5,10,20,30))
## End(Not run)