R/searchZ_sparse.R

In CorReg: Linear Regression Based on Linear Structure Between Variables

# ' Sparse structure research
# ' @param X the dataset
# ' @param Zi indices of the rows of the 1
# ' @param Zj indices of the columns of the 1
# ' @param Si rowSums vector
# ' @param Sj colSums vector
# ' @param Bic_null_vect the BIC of the null hypothesis (used for independent variables)
# '@param candidates 0:row and column,-1:column only, int>0:random int candidates, -2 : all (but the diag), -3 : non-zeros
# ' @param methode  parameter for OLS (matrix inversion) 1:householderQr, 2:colPivHouseholderQr
# '@param p1max maximum complexity for a regression
# '@param Maxiter number of steps
# '@param plot TRUE: returns for each step the type of move, complexity and BIC
# '@param best TRUE: systematically jumps to the best BIC seen ever when seen (it is stored even if best=FALSE)
# '@param better TRUE: systematically jumps to the best candidate if better than stationnarity (random wheighted jump otherwise)
# '@param random if FALSE:moves only to improve and only to the best
# '@param verbose 0:none, 1:BIC,step and complexity when best BIC found 2:BIC, step, complexity, nb candidates and best candidate when best BIC found
# '@param nb_opt_max stop criterion defining how many times the chain can walk (or stay) on the max found
# ' @param Mixmod
# ' @export
# '@return step 0:delete, 1: add, 2: stationnarity
# '
searchZ_sparse<-function(X=X,Zi=NULL,Zj=NULL,Si=NULL,Sj=NULL,Bic_null_vect=NULL,candidates=2,methode=1,p1max=5,Maxiter=1,plot=F,best=T,better=F,random=T,verbose=1,nb_opt_max=NULL){
   X=1*as.matrix(X)
   if(is.null(nb_opt_max)){
    nb_opt_max=Maxiter
  }
  if(is.null(Bic_null_vect)){
     Bic_null_vect=density_estimation(X=X)$BIC_vect 
  }
  if(is.null(Zi) | is.null(Zj) ){
     Zi=as.vector(0)
     Zj=as.vector(0)
     p=ncol(X)
     Si=rep(0,times=p)
     Sj=rep(0,times=p)
  }
  if(is.null(Si) | is.null(Sj)){
     p=ncol(X)
     Si=rep(0,times=p)
     Sj=rep(0,times=p)
     for(i in 1:p){
        Si[i]=length(which(Zi==i))
        Sj[i]=length(which(Zj==i))
     }
  }
  res=.Call( "rechercheZ_sparse_relax",X,Zi,Zj,Si,Sj,Bic_null_vect,candidates,methode,p1max,Maxiter,plot,best,better,random,verbose,nb_opt_max, PACKAGE = "CorReg")
  return(res)
}