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#' etree: Classification and Regression With Structured and Mixed-Type Data
#'
#' Implementation of Energy Trees, a statistical model to perform classification
#' and regression with structured and mixed-type data. The model has a similar
#' structure to Conditional Trees, but brings in Energy Statistics to test
#' independence between variables that are possibly structured and of different
#' nature. Currently, the package covers functions and graphs as structured
#' covariates. It builds upon 'partykit' to provide functionalities for fitting,
#' printing, plotting, and predicting with Energy Trees.
#'
#' @rawNamespace import(partykit, except = c(partynode, kidids_node,
#' fitted_node, party, predict, predict_party, edge_simple, `[`, `[[`,
#' partysplit, kidids_split, node_barplot, node_boxplot, node_surv, node_ecdf,
#' node_mvar, data_party, node_inner, nodeapply, nodeids, print, depth,
#' width))
#' @importFrom grDevices gray.colors
#' @importFrom graphics boxplot
#' @importFrom stats approxfun as.dist density dist ecdf formula knots
#' model.frame na.exclude p.adjust predict quantile terms var weighted.mean
#' @importFrom utils combn
#' @importFrom grid grid.clip grid.rect grid.layout grid.lines grid.points
#' grid.polygon grid.text grid.xaxis grid.yaxis gpar depth popViewport
#' pushViewport unit upViewport viewport
#' @importFrom survival survfit
#'
#' @docType package
#' @name etree-package
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