R/coef.sqsvmpath.R

In gcdnet: The (Adaptive) LASSO and Elastic Net Penalized Least Squares, Logistic Regression, Hybrid Huberized Support Vector Machines, Squared Hinge Loss Support Vector Machines and Expectile Regression using a Fast Generalized Coordinate Descent Algorithm

##' @export
coef.sqsvmpath <- function(object, s = NULL,
                           type = c("coefficients", "nonzero"), ...) {
  type <- match.arg(type)
  b0 <- t(as.matrix(object$b0))
  rownames(b0) <- "(Intercept)"
  nbeta <- rbind2(b0, object$beta)
  if (!is.null(s)) {
    vnames <- dimnames(nbeta)[[1]]
    dimnames(nbeta) <- list(NULL, NULL)
    lambda <- object$lambda
    lamlist <- lambda.interp(lambda, s)
    nbeta <- nbeta[, lamlist$left, drop = FALSE] %*%
      Diagonal(x = lamlist$frac) +
      nbeta[, lamlist$right, drop = FALSE] %*%
      Diagonal(x = 1-lamlist$frac)
    dimnames(nbeta) <- list(vnames, paste(seq(along = s)))
  }
  if (type == "coefficients")
    return(nbeta)
  if (type == "nonzero")
    return(nonzero(nbeta[-1, , drop = FALSE], bystep = TRUE))
}