R/glmnet.control.R

In glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models

#' internal glmnet parameters
#'
#' View and/or change the factory default parameters in glmnet
#'
#' If called with no arguments, \code{glmnet.control()} returns a list with the
#' current settings of these parameters. Any arguments included in the call
#' sets those parameters to the new values, and then silently returns. The
#' values set are persistent for the duration of the R session.
#'
#' @param fdev minimum fractional change in deviance for stopping path; factory
#' default = 1.0e-5
#' @param devmax maximum fraction of explained deviance for stopping path;
#' factory default = 0.999
#' @param eps minimum value of lambda.min.ratio (see glmnet); factory default=
#' 1.0e-6
#' @param big large floating point number; factory default = 9.9e35. Inf in
#' definition of upper.limit is set to big
#' @param mnlam minimum number of path points (lambda values) allowed; factory
#' default = 5
#' @param pmin minimum probability for any class. factory default = 1.0e-9.
#' Note that this implies a pmax of 1-pmin.
#' @param exmx maximum allowed exponent. factory default = 250.0
#' @param prec convergence threshold for multi response bounds adjustment
#' solution. factory default = 1.0e-10
#' @param mxit maximum iterations for multiresponse bounds adjustment solution.
#' factory default = 100
#' @param itrace If 1 then progress bar is displayed when running \code{glmnet}
#' and \code{cv.glmnet}. factory default = 0
#' @param epsnr convergence threshold for \code{glmnet.fit}. factory default =
#' 1.0e-6
#' @param mxitnr maximum iterations for the IRLS loop in \code{glmnet.fit}. factory
#' default = 25
#' @param factory If \code{TRUE}, reset all the parameters to the factory
#' default; default is \code{FALSE}
#' @return A list with named elements as in the argument list
#' @author Jerome Friedman, Kenneth Tay, Trevor Hastie\cr Maintainer: Trevor Hastie
#' \email{hastie@@stanford.edu}
#' @seealso \code{glmnet}
#' @keywords models regression
#' @examples
#'
#' glmnet.control(fdev = 0)  #continue along path even though not much changes
#' glmnet.control()  # view current settings
#' glmnet.control(factory = TRUE)  # reset all the parameters to their default
#'
#' @export glmnet.control
glmnet.control <-
  function (fdev = 1e-05, devmax = 0.999, eps = 1e-06, big = 9.9e+35,
            mnlam = 5, pmin = 1e-09, exmx = 250, prec = 1e-10, mxit = 100,
            itrace = 0, epsnr = 1e-06, mxitnr = 25, factory = FALSE)
{
  inquiry=!nargs()
   if (factory)
    invisible(glmnet.control(fdev = 1e-05, devmax = 0.999,
                             eps = 1e-06, big = 9.9e+35, mnlam = 5, pmin = 1e-09,
                             exmx = 250, prec = 1e-10, mxit = 100, itrace = 0,
                             epsnr = 1e-06, mxitnr = 25))
  else {
    if (!missing(fdev))
      chg_fract_dev(as.double(fdev))
    if (!missing(devmax))
      chg_dev_max(as.double(devmax))
    if (!missing(eps))
      chg_min_flmin(as.double(eps))
    if (!missing(big))
      chg_big(as.double(big))
    if (!missing(mnlam))
      chg_min_lambdas(as.integer(mnlam))
    if (!missing(pmin))
      chg_min_null_prob(as.double(pmin))
    if (!missing(exmx))
      chg_max_exp(as.double(exmx))
    if (!missing(prec) | !missing(mxit))
      chg_bnorm(as.double(prec), as.integer(mxit))
    if (!missing(itrace))
      chg_itrace(as.integer(itrace))
    if (!missing(epsnr))
        chg_epsnr(as.double(epsnr))
    if (!missing(mxitnr))
        chg_mxitnr(as.integer(mxitnr))

    value=c(get_int_parms(fdev = double(1),
                     eps = double(1), big = double(1), mnlam = integer(1),
                     devmax = double(1), pmin = double(1), exmx = double(1),
                     itrace = integer(1)),
            get_bnorm(prec = double(1), mxit = integer(1)),
            get_int_parms2(epsnr = double(1), mxitnr = integer(1)))
    if(inquiry)value else invisible(value)
  }
}