StepIII_stepwise {GDSARM} | R Documentation |
Step III: Stepwise on the consolidated output from different GDS runs
Description
Runs the stepwise regression on the output received from
top models of the consolidated output of different GDS runs. With
n
being the number of runs, the stepwise regression starts
with at most (n-3)
selected effects from the previous step. The
remaining effects from the previous step as well as all main effects are
given a chance to enter into the model using the forward-backward stepwise
regression.
Usage
StepIII_stepwise(
xstart,
xremain,
Xmain,
Xint,
Y,
cri.penter = 0.01,
cri.premove = 0.05,
opt.heredity = "none"
)
Arguments
xstart |
a vector with effects' names corresponding to the starting model. |
xremain |
a vector with effects' names corresponding to the remaining main effects and other effects that needs to be explored with stepwise regression. |
Xmain |
a |
Xint |
a matrix of |
Y |
a vector of |
cri.penter |
the p-value cutoff for the most significant effect to enter into the stepwise regression model |
cri.premove |
the p-value cutoff for the least significant effect to exit from the stepwise regression model |
opt.heredity |
a string with either |
Value
A list returning the selected effects as well as the corresponding important factors.
Source
Singh, R. and Stufken, J. (2022). Factor selection in screening experiments by aggregation over random models, 1–31. doi: 10.48550/arXiv.2205.13497