R/daprpr.R

In crmReg: Cellwise Robust M-Regression and SPADIMO

daprpr <-
  function(Data,center.type,scale.type){

    # DAPRPR Data preprocessing
    # Classical and robust scaling
    # Inputs: Data, type of centering as R function name (e.g. "mean", "l1median")
    #         type of scaling as R function name (e.g. "sd", "qn","Sn","scaleTau2")
    # Robust estimators: Please use library(robustbase)
    # Outputs: Scaled data, attributes: Data Center, Data Scale
    # Given center.type="mean" and scale.type="sd", dpp(...) is
    # equivalent to scale(Data, center=T, scale=T).
    # Written by Sven Serneels, BASF, GVM/S, June 2013.

    # require(robustbase)
    # require(pcaPP)

    if(any(is.na(Data))==TRUE){stop("Routine cannot process NAs")}
    if(missing(center.type)){center.type="median"}
    if(missing(scale.type)){scale.type="qn"}
    if(center.type=="l1median"){
      Data.center <- l1median(Data) # ? function l1median() ?
    } else {
      Data.center <- apply(Data,2,center.type)
    }
    Data.scaled <- (Data - matrix(Data.center,nrow=dim(Data)[1],ncol=dim(Data)[2],byrow=TRUE)) # ? = scale(data, center=Data.center, scale=FALSE)
    if(!(scale.type=="no")){
      Data.scale <- apply(Data,2,scale.type)
      if (any(1/Data.scale>1e19) | any(is.nan(Data.scale))){
        Data.scale <- apply(Data,2,sd)
        if (any(1/Data.scale>1e19) | any(is.nan(Data.scale))){
          Data.scale <- rep(1,ncol(Data))
          warning("Routine used scale.type='no' to avoide division by zero or infinity.")
        } else {
          warning("Routine used scale.type='sd' to avoide division by zero or infinity.")
        }
      }
      Data.scaled <- Data.scaled/matrix(Data.scale,nrow=dim(Data)[1],ncol=dim(Data)[2],byrow=TRUE)
    } else {
      Data.scale <- rep(1,ncol(Data))
    }
    attr(Data.scaled,"Center") <- Data.center
    attr(Data.scaled,"Scale") <- Data.scale
    attr(Data.scaled,"Type") <- c(center.type,scale.type)
    return(Data.scaled)
  }