#' rsample: General Resampling Infrastructure for R
#'
#'\pkg{rsample} has functions to create variations of a data set
#' that can be used to evaluate models or to estimate the
#' sampling distribution of some statistic.
#'
#' @section Terminology:
#'\itemize{
#' \item A **resample** is the result of a two-way split of a
#' data set. For example, when bootstrapping, one part of the
#' resample is a sample with replacement of the original data.
#' The other part of the split contains the instances that were
#' not contained in the bootstrap sample. The data structure
#' `rsplit` is used to store a single resample.
#' \item When the data are split in two, the portion that are
#' used to estimate the model or calculate the statistic is
#' called the **analysis** set here. In machine learning this
#' is sometimes called the "training set" but this would be
#' poorly named since it might conflict with any initial split
#' of the original data.
#' \item Conversely, the other data in the split are called the
#' **assessment** data. In bootstrapping, these data are
#' often called the "out-of-bag" samples.
#' \item A collection of resamples is contained in an
#' `rset` object.
#'}
#'
#' @section Basic Functions:
#' The main resampling functions are: [vfold_cv()],
#' [bootstraps()], [mc_cv()],
#' [rolling_origin()], and [nested_cv()].
#' @docType package
#' @name rsample
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