R/Regression.r

In GPC: Generalized Polynomial Chaos

Regression <- function(A,DesignPCE,InputDistrib,pmaxi,Output,PCSpace){
  #print("Entering Regression")
  restartAnalysis<-FALSE
  DM=DataMatrix(A,DesignPCE,InputDistrib,pmaxi,PCSpace)
  IM=t(DM)%*%DM  
  if(rcond(IM)<10^(-4)){
#   if(kappa(IM)>10^(5)){    
    R2=-10
    Q2=-10
    restartAnalysis<-TRUE
    return(list(R2=R2,Q2=Q2,rAnaly=restartAnalysis))
  } 
  else {
    #print(IM)
    InvIM=solve(IM)
    a=InvIM%*%t(DM)%*%t(t(Output))
    MetaOut=t(a)%*%t(DM) #ligne
    R2=EE(MetaOut,Output)
    #R2adj=EEadj(MetaOut)
#     print(DM)
#     print(IM)
#     print(diag(DM%*%InvIM%*%t(DM)))
    h=diag(DM%*%InvIM%*%t(DM))
    if (1 %in% h) {print('h problem'); Q2=-100; restartAnalysis=TRUE}
    else {Q2=LOO(MetaOut,diag(DM%*%InvIM%*%t(DM)),Output)}
    return(list(R2=R2,Q2=Q2,rAnaly=restartAnalysis))
   }  
}
# }