R/rotsfpca_surv_predict.R

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

# -------------------------------------------------------------------------------
#   This file is part of Rotsf.
#
# Rotsf is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Rotsf is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Rotsf. If not, see <http://www.gnu.org/licenses/>.
#
# Written by:
#
#   Hong Wang
# 
# http://www.csu.edu.cn
# wh@csu.edu.cn
# -------------------------------------------------------------------------------

##' Prediction with new data and return a saved forest with survival proability at.
##' Each unique time points
##' @export
rotsfpca.surv_predict <-
function(rotsfpcafit,newdata,uniquetimes,trlength=500){
  
  trees=rotsfpcafit$pectrees
  rotms=rotsfpcafit$rotms
  rii=rotsfpcafit$rii
  
  if (trlength>length(rotsfpcafit$rotms))
    stop("Number of Trees for prediction should not be more than Number of Trees Fitted")
  
 
  # Preparing testpre dataframe 
  testpre <- matrix(0,nrow = dim(newdata)[1],  ncol= length(uniquetimes))
  colnames(testpre)=paste0(uniquetimes)
  
  for (i in 1:trlength) {
    #if (oobacc[i]<=avroobacc)
    {
      
      # preparing for testing
      rmatrix2=as.matrix(newdata) %*% t(rotms[[i]])
      rmatrixnew2=as.data.frame(rmatrix2)
      
      colnames(rmatrixnew2)=colnames(newdata)
      
    
      
      predicts=predictSurvProb(trees[[i]],rmatrixnew2,uniquetimes)
      #convert all NA into zero
      predicts[is.na(predicts)]=0
      colnames(predicts)=paste0(uniquetimes)
      #print((predicts[1,100]))
      testpre<-testpre+predicts
    }
  }
  
  return(testpre/trlength)
  
}