#' imputation for predictive analytics - ipa.
#'
#' ipa provides functions to help you design and use effective
#' strategies to handle missing data.
#'
#' To learn more about ipa, start with the vignettes:
#' `browseVignettes(package = "ipa")`
#'
#' @importFrom rlang %||%
#' @importFrom stats median na.omit coef predict
#' @import data.table
#'
#'
#'
"_PACKAGE"
## quiets concerns of R CMD check re: the .'s that appear in pipelines
if(getRversion() >= "2.15.1") utils::globalVariables(
c(".",
'fit',
'name',
'type',
'value',
'score',
'..cols',
'..keep',
'..outcome',
'..par_cols',
'..keep_cols',
'..val_names',
'..impute_prds',
'impute',
'lambda',
'aggr_fun',
'variable',
'n_impute',
'node_size',
'donor_size',
'k_neighbors',
'rank_max',
'rank_fit',
'pars',
'rank_max_init',
'rank_max_ovrl',
'rank_stp_size'
)
)
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