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disaggR

Two-Steps Benchmarks for Time Series Disaggregation

v1.0.5.4 · Nov 3, 2025 · MIT + file LICENSE

Description

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>).

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies RColorBrewer disaggR

Version History

new 1.0.5.4 Mar 10, 2026
updated 1.0.5.4 ← 1.0.5.3 diff Nov 3, 2025
updated 1.0.5.3 ← 1.0.5.2 diff Jul 10, 2024
updated 1.0.5.2 ← 1.0.5.1 diff Feb 8, 2024
updated 1.0.5.1 ← 1.0.5 diff Oct 6, 2023
updated 1.0.5 ← 1.0.4.1 diff Feb 20, 2023
updated 1.0.4.1 ← 1.0.3.1 diff Dec 12, 2022
updated 1.0.3.1 ← 1.0.3 diff Mar 3, 2022
updated 1.0.3 ← 1.0.2 diff Feb 21, 2022
updated 1.0.2 ← 1.0.1 diff Aug 22, 2021
updated 1.0.1 ← 1.0.0 diff Jul 20, 2021
updated 1.0.0 ← 0.2.1 diff Jun 17, 2021
updated 0.2.1 ← 0.2.0.3 diff May 2, 2021
updated 0.2.0.3 ← 0.2.0.2 diff Apr 10, 2021
updated 0.2.0.2 ← 0.1.11 diff Apr 9, 2021
updated 0.1.11 ← 0.1.9 diff Dec 8, 2020
updated 0.1.9 ← 0.1.8 diff Oct 11, 2020
updated 0.1.8 ← 0.1.7 diff Oct 9, 2020
updated 0.1.7 ← 0.1.6 diff Oct 8, 2020
updated 0.1.6 ← 0.1.5 diff Aug 24, 2020