predict.glmreg {mpath} | R Documentation |
Model predictions based on a fitted "glmreg" object.
Description
This function returns predictions from
a fitted "glmreg"
object.
Usage
## S3 method for class 'glmreg'
predict(object,newx,newoffset,which=1:length(object$lambda),
type=c("link","response","class","coefficients","nonzero"), na.action=na.pass, ...)
## S3 method for class 'glmreg'
coef(object,which=1:length(object$lambda),...)
Arguments
object |
Fitted |
newx |
Matrix of values at which predictions are to be made. Not
used for |
which |
Indices of the penalty parameter |
type |
Type of prediction: |
newoffset |
an offset term used in prediction |
na.action |
action for missing data value |
... |
arguments for predict |
Value
The returned object depends on type
.
Author(s)
Zhu Wang <zwang145@uthsc.edu>
References
Zhu Wang, Shuangge Ma, Michael Zappitelli, Chirag Parikh, Ching-Yun Wang and Prasad Devarajan (2014) Penalized Count Data Regression with Application to Hospital Stay after Pediatric Cardiac Surgery, Statistical Methods in Medical Research. 2014 Apr 17. [Epub ahead of print]
See Also
Examples
## Dobson (1990) Page 93: Randomized Controlled Trial :
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
print(d.AD <- data.frame(treatment, outcome, counts))
fit <- glmreg(counts ~ outcome + treatment, data=d.AD, family="poisson")
predict(fit, newx=d.AD[,1:2])
summary(fit)
coef(fit)