About Anaconda Help Download Anaconda

r / packages / r-disaggr

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>).

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/r/r-disaggr/badges/version.svg
badge
https://anaconda.org/r/r-disaggr/badges/latest_release_date.svg
badge
https://anaconda.org/r/r-disaggr/badges/latest_release_relative_date.svg
badge
https://anaconda.org/r/r-disaggr/badges/platforms.svg
badge
https://anaconda.org/r/r-disaggr/badges/license.svg
badge
https://anaconda.org/r/r-disaggr/badges/downloads.svg

© 2025 Anaconda, Inc. All Rights Reserved. (v4.0.6) Legal | Privacy Policy