R/superpc.train.R

In superpc: Supervised Principal Components

superpc.train <- function (data, 
                           type=c("survival","regression"), 
                           s0.perc=NULL){

    # computes feature scores for supervised pc analysis
    
    this.call <- match.call()
    type <- match.arg(type)

    if (is.null(data$censoring.status) & type == "survival") {
        stop("Error: survival specified but  censoring.status is null")
    }
    if (!is.null(data$censoring.status) & type == "regression") {
        stop("Error: regression specified but  censoring.status is  non-null")
    }
    if (type == "survival") {
        junk <- coxfunc(data$x, data$y, data$censoring.status, s0.perc=s0.perc)
        feature.scores <- junk$tt
    } else {
        junk <- cor.func(data$x, data$y, s0.perc=s0.perc)
        feature.scores <- junk$tt
    }
    junk <- list(feature.scores=feature.scores, 
                 type=type, 
                 s0.perc=s0.perc, 
                 call=this.call)
    class(junk) <- "superpc"
    
    return(junk)

}