predict.glmnetr {glmnetr} | R Documentation |
Get predicteds or coefficients using a glmnetr output object
Description
Give predicteds based upon a glmnetr() output object. Because the glmnetr() function has no cross validation information, lambda and gamma must be specified. To choose lambda and gamma based upon cross validation one may use the cv.glmnetr() or nested.glmnetr() and the corresponding predict() functions.
Usage
## S3 method for class 'glmnetr'
predict(object, xs_new = NULL, lam = NULL, gam = NULL, ...)
Arguments
object |
A glmnetr output object |
xs_new |
A desing matrix for predictions |
lam |
The value for lambda for determining the lasso fit. Required. |
gam |
The value for gamma for determining the lasso fit. Required. |
... |
Additional arguments passed to the predict function. |
Value
Coefficients or predictions using a glmnetr output object. When outputting coefficients (beta), creates a list with the first element, beta_, including 0 and non-0 terms and the second element, beta, including only non 0 terms.
See Also
glmnetr
, cv.glmnetr
, nested.glmnetr
Examples
set.seed(82545037)
sim.data=glmnetr.simdata(nrows=200, ncols=100, beta=NULL)
xs=sim.data$xs
y_=sim.data$yt
event=sim.data$event
glmnetr.fit = glmnetr( xs, NULL, y_, event, family="cox")
betas = predict(glmnetr.fit,NULL,exp(-2),0.5 )
betas$beta