Package: deseats
Type: Package
Title: Data-Driven Locally Weighted Regression for Trend and
        Seasonality in TS
Version: 1.1.3
Date: 2026-10-11
Authors@R: 
    c(person(given = "Yuanhua",
             family = "Feng",
             role = "aut",
             comment = "Paderborn University, Germany"),
      person(given = "Dominik",
             family = "Schulz",
             role = c("aut", "cre"),
             email = "dominik.schulz.r@gmail.com",
             comment = "formerly Paderborn University, Germany"))
Maintainer: Dominik Schulz <dominik.schulz.r@gmail.com>
Description: Various methods for the identification of trend and
        seasonal components in time series (TS) are provided. Among
        them is a data-driven locally weighted regression approach with
        automatically selected bandwidth for equidistant short-memory
        time series. The approach is a combination / extension of the
        algorithms by Feng (2013) <doi:10.1080/02664763.2012.740626>
        and Feng, Y., Gries, T., and Fritz, M. (2020)
        <doi:10.1080/10485252.2020.1759598> and a brief description of
        this new method is provided in the package documentation and in
        more detail in Schulz (2026) <doi:10.32614/RJ-2026-025>.
        Furthermore, the package allows its users to apply the base
        model of the Berlin procedure, version 4.1, as described in
        Speth (2004)
        <https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=publicationFile>.
        Permission to include this procedure was kindly provided by the
        Federal Statistical Office of Germany.
Imports: Rcpp (>= 1.0.6), ggplot2, stats, graphics, animation, utils,
        shiny, tools, zoo, future, furrr, future.apply, progressr,
        purrr, rlang, tidyr
License: GPL-3
Encoding: UTF-8
URL: https://github.com/dschulz13/deseats
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 2.10), methods
Suggests: badger, knitr, rmarkdown, smoots, testthat (>= 3.0.0)
LazyData: true
Collate: 'AttachMessage.R' 'RcppExports.R' 'generics.R'
        'helper_functions.R' 'subplot_functions.R'
        'accuracy_measures.R' 'class-smoothing_options.R'
        'class-decomp.R' 'class-deseats.R' 'class-s_semiarma.R'
        'class-bv41.R' 'class-hfilter.R' 'class-lmdecomp.R'
        'class-madecomp.R' 'class-llindecomp.R' 'data_documentation.R'
        'fitting_functions.R' 'runDecomposition.R' 'class-deseats_fc.R'
        'forecasting_functions.R' 'bwidth_bootstrap.R'
        'gain_function.R' 'linear_filters.R' 'ts_conversion.R'
        'hA_calc.R' 'arima_no_warn.R' 'deseats-package.R'
        'seasonplot.R'
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/roxygen2/version: 8.1.0
Config/pak/sysreqs: cmake make libmagick++-dev gsfonts texlive
        libicu-dev libuv1-dev libssl-dev zlib1g-dev
Repository: https://dschulz13.r-universe.dev
Date/Publication: 2026-10-11 09:41:29 UTC
RemoteUrl: https://github.com/dschulz13/deseats
RemoteRef: HEAD
RemoteSha: 6c60aa455b802689c0db3d812afddd6288c1f661
NeedsCompilation: yes
Packaged: 2026-10-11 11:11:18 UTC; root
Author: Yuanhua Feng [aut] (Paderborn University, Germany),
  Dominik Schulz [aut, cre] (formerly Paderborn University, Germany)