| penalizedS3 | R Documentation | 
S3-wrapper for S4 function penalized
penalizedS3(formula, data, type = "elastic.net", lambda1, lambda2, fold, ...)
| formula | Communicated outcome and explanatory variables. See examples. | 
| data | Data set in which formula is to be interpreted | 
| type | String specifying the type of penalization. Should match one of the following values:
 | 
| lambda1 | Lasso penalty | 
| lambda2 | ridge penalty | 
| fold | passed to  | 
| ... | Arguments passed to penalized | 
library(prodlim)
## Not run: 
## too slow
if (require("penalized",quietly=TRUE)){
library(penalized)
set.seed(8)
d <- sampleData(200,outcome="binary")
newd <- sampleData(80,outcome="binary")
fitridge <- penalizedS3(Y~X1+X2+pen(7:8), data=d, type="ridge",
                standardize=TRUE, model="logistic",trace=FALSE)
fitlasso <- penalizedS3(Y~X1+X2+pen(7:8), data=d, type="lasso",
                standardize=TRUE, model="logistic",trace=FALSE)
# fitnet <- penalizedS3(Y~X1+X2+pen(7:8), data=d, type="elastic.net",
# standardize=TRUE, model="logistic",trace=FALSE)
predictRisk(fitridge,newdata=newd)
predictRisk(fitlasso,newdata=newd)
# predictRisk(fitnet,newdata=newd)
Score(list(fitridge),data=newd,formula=Y~1)
Score(list(fitridge),data=newd,formula=Y~1,split.method="bootcv",B=2)
data(nki70) ## S4 fit
fitS4 <- penalized(Surv(time, event), penalized = nki70[,8:77],
                 unpenalized = ~ER+Age+Diam+N+Grade, data = nki70,
                 lambda1 = 1)
fitS3 <- penalizedS3(Surv(time,event)~ER+Age+Diam+pen(8:77)+N+Grade,
                     data=nki70, lambda1=1)
## or
penS3 <- penalizedS3(Surv(time,event)~ER+pen(TSPYL5,Contig63649_RC)+pen(10:77)+N+Grade,
                     data=nki70, lambda1=1)
## also this works
penS3 <- penalizedS3(Surv(time,event)~ER+Age+pen(8:33)+Diam+pen(34:77)+N+Grade,
                    data=nki70, lambda1=1)
}
## End(Not run)
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