| predict.logilasso {logilasso} | R Documentation |
Predicts the interaction vector beta of a loglinear interaction
model.
Description
Predicts the interaction vector(s) beta of a loglinear model
log(p)=X*beta, fitted either
by logilasso or levelcv. If lambda is specified,
this lambda is taken to predict the beta for this value of lambda. If no
value for lambda is specified, then the optimal value calculated
by cross-validation is taken for objects of class
cvlogilasso. For objects of class logilasso where no
cross-validation was performed, the whole solution path for all lambdas
is returned.
Usage
## S3 method for class 'logilasso':
predict(object, lambda = NULL, ...)
## S3 method for class 'cvlogilasso':
predict(object, lambda = NULL, ...)
## S3 method for class 'levellogilasso':
predict(object, lambda = NULL, to.which.int =
NULL, ...)
Arguments
object |
Object of class levellogilasso, cvlogilasso or class logilasso. |
lambda |
Value for the penalization parameter lambda,
for which the corresponding beta should be calculated. |
to.which.int |
The number of factors the model should be
predicted for. |
... |
Additional arguments to predict function. |
Value
Is either an object of class predlogilasso if a value for
lambda was specified or if the optimal lambda can was
assessed by cross-validation. Otherwise, if no value for lambda
was specified and at the same time cvfold was chosen to be 1
(no cross-validation) it is of class predlogispez. The
difference between these two classes is described below.
beta |
A predicted value for beta if the object is of class
predlogilasso. For the class predlogispez this is a
matrix consisting of the columns beta for the whole solution
path. |
lambda |
The lambda(s) for which the beta(s) was/were calculated. |
probs |
Probabilities according to the model probs=exp(X*beta) |
nls |
Negative likelihood score. For details see http://stat.ethz.ch/~dahinden/Paper/BMC.pdf |
betapath |
The whole solution originally calculated path. For objects of class
predlogispez this equals beta. |
lambdapath |
The lambdas corresponding to the value betapath. |
losspath |
nls for the whole solution path. |
See Also
logilasso
Examples
library(gRbase)
data(reinis)
fit <- logilasso(reinis,lambdainit=1,lambdamin=0.1)
pred1 <- predict(fit,lambda=0.5)
pred2 <- predict(fit)
fitcv <- logilasso(reinis,lambdainit=1,lambdamin=0.1,cvfold=3)
predcv1 <- predict(fitcv)
levellogi <- levelcv(reinis,lambdainit=1,lambdamin=0.1,to.which.int=3,cvfold=3)
predlevel <- predict(levellogi)
## Methods plot and graphmod exist for all predicted models
## Except for pred2, there is no graphmod method, because no
## lambda was specified
plot(predcv1)
graphmod(predcv1)
[Package
logilasso version 0.1.0
Index]