# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
#' @title FPOP2D
#'
#' @description Detecting changepoints using the functional pruning optimal partitioning method (fpop) in bivariate time series.
#'
#' @param data1 is a vector of data1(a univariate time series).
#' @param data2 is a vector of data2(a univariate time series).
#' @param penalty is a value of penalty (a non-negative real number).
#' @param type is a value defining the type of pruning (0 = PELT, 1 = FPOP(intersection of sets), 2 = FPOP(intersection of set \ union of set ).
#'
#' @return a list of 4 elements = (changepoints, means1, means2, globalCost).
#'
#' \describe{
#' \item{\code{changepoints}}{is the vector of changepoints.}
#' \item{\code{means1}}{is the vector of successive means for data1.}
#' \item{\code{means2}}{is the vector of successive means for data2.}
#' \item{\code{globalCost}}{is a number equal to the global cost.}
#' } #
#'
#' @examples FPOP2D (data1 = c(0,0,0,1,1,1), data2 = c(2,2,2,0,0,0), penalty = 2*log(6), type = 1)
FPOP2D <- function(data1, data2, penalty, type) {
.Call(`_fpop2D_FPOP2D`, data1, data2, penalty, type)
}
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