predict.rrotsfspls: rotsf predict.rrotsfspls

In whcsu/rotsf: Survival Forest with PCA and Partial Least Squares

Description

Prediction with rrotsfspls and return a list of with mean hazard function

Usage

## S3 method for class 'rrotsfspls'
predict(object, testx, trlength = object$trlength, ...)

Arguments

object	An object that inherits from class rrotsfspls.
testx	A data frame in which to look for variables with which to predict.
trlength	Number of based models used for prediction, shouble be less than and equal to the number for training.
...	Additional arguments.

Value

produces a vector of predictions or a matrix of predictions

Author(s)

Hong Wang and Lifeng Zhou

References

• Zhou L, Xu Q, Wang H. (2015) Rotation survival forest for right censored data. PeerJ 3:e1009 https://doi.org/10.7717/peerj.1009.

• Zhou, L., Wang, H., & Xu, Q. (2016). Random rotation survival forest for high dimensional censored data. SpringerPlus, 5(1), 1425.

See Also

pec R package

Examples

set.seed(123)
require(rotsf)
require(survival)
## Survival Forest with PLS  with default settings
#Lung DATA
data(lung)
lung=na.omit(lung)
lung[,3]=lung[,3]-1
n=dim(lung)[1]
L=sample(1:n,ceiling(n*0.5))
trset<-lung[L,]
teset<-lung[-L,]
rii=c(2,3)
plssurvmodel=rrotsfspls(x=trset[,-rii],y=Surv(trset[,rii[1]], trset[,rii[2]]))
mypre=predict(plssurvmodel, teset[,-rii])

whcsu/rotsf documentation built on Dec. 4, 2019, 2:10 p.m.