R/imputeTS-package.R

In imputeTS: Time Series Missing Value Imputation

#' @keywords internal
"_PACKAGE"

#' @title imputeTS-package description
#' 
#' @description 
#' The imputeTS package is a collection of algorithms and tools for univariate time series imputation.
#' 
#' @details The imputeTS package specializes on (univariate) time series imputation. 
#' It offers several different imputation algorithm implementations. Beyond the imputation algorithms 
#' the package also provides plotting and printing functions of missing data statistics.
#' 
#' The package is easy to use:
#' 
#' - To impute (fill all missing values) in a time series \code{x}, run:\cr
#'  \code{na_interpolation(x)} \cr
#'          
#' - To plot missing data statistics for a time series \code{x}, run:\cr
#'  \code{ggplot_na_distribution(x)}\cr
#'
#' - To print missing data statistics for a time series \code{x}, run:\cr
#'  \code{statsNA(x)}\cr
#' 
#' Every other imputation function (starting with na_'algorithm name') and plotting
#' function (starting with plotNA_'plot name') work the same way as in this example.
#'   
#' @name imputeTS-package
#' 
#' @references Moritz, Steffen, and Thomas Bartz-Beielstein. "imputeTS: Time Series Missing Value Imputation in R." R Journal 9.1 (2017). doi:10.32614/RJ-2017-009.
#' 
#' @import stats
#' @importFrom magrittr %>%
#' @importFrom utils globalVariables
#' @importFrom Rcpp sourceCpp
#' @useDynLib imputeTS
NULL

.onUnload <- function (libpath) {
  library.dynam.unload("imputeTS", libpath)
}

utils::globalVariables(c("rule"))

#' @export 
magrittr::`%>%`