"stepwise"(object, criterion = "aic", alpha = NULL, type ="decomposable", search="all", steps = 1000, k = 2, direction = "backward", fixinMAT=NULL, fixoutMAT=NULL, details = 0, trace = 2, ...)
backward(object, criterion = "aic", alpha = NULL, type = "decomposable", search="all", steps = 1000, k = 2, fixinMAT=NULL, details = 1, trace = 2,...)
forward(object, criterion = "aic", alpha = NULL, type = "decomposable", search="all", steps = 1000, k = 2, fixoutMAT=NULL, details = 1, trace = 2,...)
iModel
model object"aic"
or "test"
(for
significance test)criterion="aic"
, alpha
defaults to
0; when criterion="test"
, alpha
defaults to 0.05."decomposable"
or
"unrestricted"
. If type="decomposable"
and the initial
model is decompsable, then the search is among decomposable models
only. 'all'
(greedy) or 'headlong'
(search edges randomly; stop when an improvement has been found).criterion="aic"
. Only k=2 gives
genuine AIC."backward"
or "forward"
.testdelete
(for testInEdges
) and testadd
(for testOutEdges
). iModel
model object.
cmod
dmod
mmod
testInEdges
testOutEdges
data(reinis)
## The saturated model
m1 <- dmod(~.^., data=reinis)
m2 <- stepwise(m1)
m2
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