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#' Matrix Profile for R
#'
#' This package is derived from the former package `tsmp`. It is intended to make a clear separation of what is the
#' Matrix Profile computation and what are the data mining process we can do using Matrix Profile.
#'
#' @details
#' The Matrix Profile, has the potential to revolutionize time series data mining because of its generality,
#' versatility, simplicity and scalability. In particular it has implications for time series motif discovery, time
#' series joins, shapelet discovery (classification), density estimation, semantic segmentation, visualization, rule
#' discovery, clustering etc.
#'
#' # Parallel backend
#'
#' This package uses RcppParallel in order to do multithreading computations. By default it uses the 'TBB' backend.
#' If por any reason you want to change the backend to 'tinythread', you may use:
#' `Sys.setenv(RCPP_PARALLEL_BACKEND = "tinythread")`. To configure back to 'TBB', use
#' `Sys.setenv(RCPP_PARALLEL_BACKEND = "tbb")`.
#'
#'
#' @references * Yeh CCM, Zhu Y, Ulanova L, Begum N, Ding Y, Dau HA, et al. Matrix profile I: All pairs similarity joins
#' for time series: A unifying view that includes motifs, discords and shapelets. Proc - IEEE Int Conf Data Mining,
#' ICDM. 2017;1317-22.
#' @references * Zhu Y, Imamura m, Nikovski D, Keogh E. Matrix Profile VII: Time Series Chains: A New Primitive for Time
#' Series Data Mining. Knowl Inf Syst. 2018 Jun 2;1-27.
#' @references * Zhu Y, Zimmerman Z, Senobari NS, Yeh CM, Funning G. Matrix Profile II : Exploiting a Novel Algorithm
#' and GPUs to Break the One Hundred Million Barrier for Time Series Motifs and Joins. Icdm. 2016 Jan 22;54(1):739-48.
#' @references Website: <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>
#'
#' @name matrixprofiler
#' @rdname matrixprofiler
## usethis namespace: start
#' @useDynLib matrixprofiler, .registration = TRUE
## usethis namespace: end
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## usethis namespace: start
#' @importFrom Rcpp sourceCpp
## usethis namespace: end
#' @importFrom RcppParallel RcppParallelLibs
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