R/zzz.R

In mlim: Single and Multiple Imputation with Automated Machine Learning

#' @title normalized RMSE
#' @description calculates the normalized RMSE
#' @importFrom curl curl
#' @author E. F. Haghish
#' @keywords Internal
#' @noRd
#'
.onAttach <- function(lib, pkg) {
  packageStartupMessage('Single and Multiple Imputation with Automated Machine Learning\nhttps://github.com/haghish/mlim\n\nNote1: The package receives frequent updates. Installing \n       the development version from GitHub is recommended. \n       Also note that multiple imputation feature, in contrast to \n       single imputation, is work-in-progress and not yet stable.\n       the stochastic solution (i.e., stochastic = TRUE) is \n       currently available, but still under testing...\nNote2: The default algorithm is ELNET, which is the fastest\n       to fine-tune. You can reduce imputation error by\n       adding other algorithms e.g. "RF", "Ensemble", ...\nNote3: If you find a bug, post it on GitHub or e-mail it to \n       haghish@uio.no\n')
  options("prefer_RCurl" = FALSE)
  options(timeout = 3600) # "seconds"
}