Stepwise model selection in (graphical) interaction models
Stepwise model selection in (graphical) interaction models
drop_func(criterion) ## S3 method for class 'iModel' stepwise( object, criterion = "aic", alpha = NULL, type = "decomposable", search = "all", steps = 1000, k = 2, direction = "backward", fixin = NULL, fixout = NULL, details = 0, trace = 2, ... ) backward( object, criterion = "aic", alpha = NULL, type = "decomposable", search = "all", steps = 1000, k = 2, fixin = NULL, details = 1, trace = 2, ... ) forward( object, criterion = "aic", alpha = NULL, type = "decomposable", search = "all", steps = 1000, k = 2, fixout = NULL, details = 1, trace = 2, ... )
criterion |
Either |
object |
An |
alpha |
Critical value for deeming an edge to be significant/
insignificant. When |
type |
Type of models to search. Either |
search |
Either |
steps |
Maximum number of steps. |
k |
Penalty term when |
direction |
Direction for model search. Either |
fixin |
Matrix (p x 2) of edges. If those edges are in the model, they are not considered for removal. |
fixout |
Matrix (p x 2) of edges. If those edges are not in the model, they are not considered for addition. |
details |
Controls the level of printing on the screen. |
trace |
For debugging only |
... |
Further arguments to be passed on to |
Søren Højsgaard, sorenh@math.aau.dk
data(reinis) ## The saturated model m1 <- dmod(~.^., data=reinis) m2 <- stepwise(m1) m2
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.