Package: disaggR 1.0.5.3

Pauline Meinzel

disaggR: Two-Steps Benchmarks for Time Series Disaggregation

The twoStepsBenchmark() and threeRuleSmooth() functions allow you to disaggregate a low-frequency time series with higher frequency time series, using the French National Accounts methodology. The aggregated sum of the resulting time series is strictly equal to the low-frequency time series within the benchmarking window. Typically, the low-frequency time series is an annual one, unknown for the last year, and the high frequency one is either quarterly or monthly. See "Methodology of quarterly national accounts", Insee Méthodes N°126, by Insee (2012, ISBN:978-2-11-068613-8, <https://www.insee.fr/en/information/2579410>).

Authors:Arnaud Feldmann [aut], Pauline Meinzel [cre], Thomas Laurent [ctb], Franck Arnaud [ctb], Institut national de la statistique et des études économiques [cph]

disaggR_1.0.5.3.tar.gz
disaggR_1.0.5.3.zip(r-4.5)disaggR_1.0.5.3.zip(r-4.4)disaggR_1.0.5.3.zip(r-4.3)
disaggR_1.0.5.3.tgz(r-4.4-any)disaggR_1.0.5.3.tgz(r-4.3-any)
disaggR_1.0.5.3.tar.gz(r-4.5-noble)disaggR_1.0.5.3.tar.gz(r-4.4-noble)
disaggR_1.0.5.3.tgz(r-4.4-emscripten)disaggR_1.0.5.3.tgz(r-4.3-emscripten)
disaggR.pdf |disaggR.html
disaggR/json (API)
NEWS

# Install 'disaggR' in R:
install.packages('disaggR', repos = c('https://inseefr.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/inseefr/disaggr/issues

Datasets:

    On CRAN:

    disaggregationstatistical-packagetime-series

    6.65 score 12 stars 31 scripts 478 downloads 27 exports 1 dependencies

    Last updated 5 months agofrom:c2a531babc. Checks:OK: 7. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKNov 11 2024
    R-4.5-winOKNov 11 2024
    R-4.5-linuxOKNov 11 2024
    R-4.4-winOKNov 11 2024
    R-4.4-macOKNov 11 2024
    R-4.3-winOKNov 11 2024
    R-4.3-macOKNov 11 2024

    Exports:annualBenchmarkbflSmoothdefault_col_paldefault_lty_paldefault_marginsdefault_theme_ggplotdistancein_disaggrin_revisionsin_samplein_scatterMath2model.listOpsoutlierspraisrePortresiduals_extrapreUseBenchmarkreViewrhoseshowsmoothed.partsmoothed.ratethreeRuleSmoothtwoStepsBenchmark

    Dependencies:RColorBrewer

    Introduction to disaggR

    Rendered fromdisaggr.Rmdusingknitr::rmarkdownon Nov 11 2024.

    Last update: 2022-02-28
    Started: 2021-08-16

    Outliers in two-step benchmarks

    Rendered fromdisaggr_outlier.Rmdusingknitr::rmarkdownon Nov 11 2024.

    Last update: 2022-07-19
    Started: 2022-07-19