R/summary.ridgeLinear.R

In ridge: Ridge Regression with Automatic Selection of the Penalty Parameter

## summary function for ridgeLinear object

#' @rdname summary
#' @export
#' @importFrom stats coef
summary.ridgeLinear <- function(object, all.coef = FALSE, ...)
  {
    res <- vector("list")
    isScaled <- object$isScaled
    Inter <- object$Inter
    res$automatic <- object$automatic
    res$call <- object$call
    res$lambda <- object$lambda
    pvalues <- pvals(object)
    summaries <- vector("list", length(res$lambda))
    res$all.coef = all.coef
    coefs <- rbind(coef(object, all.coef = TRUE))
    if(res$automatic)
      {
        res$chosen.nPCs <- object$chosen.nPCs
      }
    for(i in seq(length(res$lambda)))
      {
        summary <- vector("list")
        if(Inter)
          {
            if(isScaled)
              {
                ## Intercept and scaled
                summary$coefficients <- cbind(coefs[i,], c(NA, object$coef[,i]), c(NA, pvalues$se[,i]), c(NA, pvalues$tstat[,i]), c(NA, pvalues$pval[,i]))
                dimnames(summary$coefficients) <- list(c("(Intercept)", colnames(object$x)), c("Estimate", "Scaled estimate", "Std. Error (scaled)", "t value (scaled)", "Pr(>|t|)"))
              } else {
                ## Intercept, no scaling
                summary$coefficients <- cbind(coefs[i,], c(NA, pvalues$se[,i]), c(NA, pvalues$tstat[,i]), c(NA, pvalues$pval[,i]))
                dimnames(summary$coefficients) <- list(c("(Intercept)", colnames(object$x)), c("Estimate", "Std. Error", "t value", "Pr(>|t|)"))
              }
          } else {
            if(isScaled)
              {
                summary$coefficients <- cbind(coefs[i,], object$coef[,i], pvalues$se[,i], pvalues$tstat[,i],  pvalues$pval[,i])
                dimnames(summary$coefficients) <- list(colnames(object$x), c("Estimate", "Scaled estimate", "Std. Error (scaled)", "t value (scaled)", "Pr(>|t|)"))
              } else {
                ## No intercept, no scaling
                summary$coefficients <- cbind(coefs[i,], pvalues$se[,i], pvalues$tstat[,i], pvalues$pval[,i])
                dimnames(summary$coefficients) <- list(colnames(object$x), c("Estimate", "Std. Error", "t value", "Pr(>|t|)"))
              }
          }
        ## df: degrees of freedom: model, variance, residual
        summary$df <- object$df[i,]
        if(!is.null(object$max.nPCs))
          {
            summary$nPCs <- i
          }
        summary$lambda <- object$lambda[i]
        summaries[[i]] <- summary
        names(summaries)[[i]] <- paste("summary", i, sep = "")
        rm(summary)
      } ## Ends for i in seq(length(res$lambda))
    res$summaries <- summaries
    ## Make an object of class summary.ridgeLinear
    class(res) <- "summary.ridgeLinear"
    ## Call its print method (print.summary.ridgeLinear)
    res
  }