R/readZ.R

In CorReg: Linear Regression Based on Linear Structure Between Variables

#' read the structure and explain it
#' @description This function describes the structure of sub-regression given by an adjacency matrix. It computes the associated regression coefficients and R-squared for each sub-regression.
#'@param Z binary adjacency matrix of the structure (size p)
#' @param B is the complete structure (Z with sub-regression coefficients instead of 1 and an additional first line for the intercepts)
#' @param crit define the criterion to use: c("none","R2","F","sigmaX")
#' @param varnames the names of the variables (size p)
#' @param output indicates the content of the output: c("index","names","all")
#' @param X is a data frame or matrix containing the dataset
#' @param order define the order used (0: none, -1: decreasing, 1: growing) for printing
#' @return a list containing the sub-regressions details. Each item of the list represents 
#' a subregression. First element is the R-square.Second element is the variable that is regressed by others.
#' Then comes the list of the explicative variables in the subgression and the associated coefficients (in the first column).
#' @examples
#' \donttest{
#' 
#' data<-mtcars
#' #we first search a sub-regression structure
#' res=structureFinder(X = data,nbini = 30,verbose=0)
#' #then we can try to interpret it
#' readZ(Z = res$Z_opt,crit = "R2",output = "all",X = data)
#' #each component is a sub-regression
#' #First line : The adjusted R-squared is given
#' #Second line : the name of the covariate that is regressed by others
#' #other lines : Coefficients of sub-regression and name of the associated covariate
#' }
#' @export
readZ<-function(Z=Z,B=NULL,crit=c("none","R2","F","sigmaX"),varnames=NULL,output=c("index","names","all"),X=NULL,order=1){
  p=ncol(Z)
  output=output[1]
  res=list()
  if(output!="index" & is.null(varnames)){#if names needed but unknown
    if(length(names(X))!=p){
      varnames=1:p
    }else{
      varnames=names(X)
    }
  }
  if(is.null(B) & (crit!="none"| output=="all")){#if B needed but unknown
     B=hatB(Z=Z,X=X)
  }
  if(crit!="none"){
    R2vect=R2Z(Z=Z,X=X,adj=TRUE,crit=crit)
    R2vect=R2vect[R2vect!=0]
    quiI2=which(colSums(Z)!=0)
    if(order==1){#increasing order
       neworder=order(R2vect,decreasing=FALSE)
       
    }else if(order==-1){
       neworder=order(R2vect,decreasing=TRUE)
       
    }else{
       neworder=1:length(quiI2)     
    }
    if(output=="index"){
      for(i in 1:length(quiI2)){
        res[[i]]=c(quiI2[neworder[i]],which(Z[,quiI2[neworder[i]]]!=0))
      }
    }else if(output=="names"){
      for(i in 1:length(quiI2)){
        res[[i]]=varnames[c(quiI2[neworder[i]],which(Z[,quiI2[neworder[i]]]!=0))]
      }
    }else{#all
      for(i in 1:length(quiI2)){
        beta=B[,quiI2[neworder[i]]]
        ssreg=data.frame(cbind(c(R2vect[neworder[i]],NA,beta[beta!=0]),c(crit,varnames[quiI2[neworder[i]]],"intercept",varnames[which(Z[,quiI2[neworder[i]]]!=0)])))
        names(ssreg)=c("coefs","var")
        res[[i]]=ssreg
      }
    }
  }else{
    quiI2=which(colSums(Z)!=0)
    if(output=="index"){
      for(i in 1:length(quiI2)){
        res[[i]]=c(quiI2[i],which(Z[,quiI2[i]]!=0))
      }
    }else if(output=="names"){
      for(i in 1:length(quiI2)){
        res[[i]]=varnames[c(quiI2[i],which(Z[,quiI2[i]]!=0))]
      }
    }else{#all
      for(i in 1:length(quiI2)){
        beta=B[,quiI2[i]]
        ssreg=data.frame(cbind(c(NA,beta[beta!=0]),c(varnames[quiI2[i]],"intercept",varnames[which(Z[,quiI2[i]]!=0)])))
        names(ssreg)=c("coefs","var")
        res[[i]]=ssreg
      }
    }
  }
  return(res)
}