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>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.5.4 |
rolling linux/jammy R-4.5 | disaggR_1.0.5.4.tar.gz |
880.3 KiB |
1.0.5.4 |
rolling linux/noble R-4.5 | disaggR_1.0.5.4.tar.gz |
880.0 KiB |
1.0.5.4 |
rolling source/ R- | disaggR_1.0.5.4.tar.gz |
1.1 MiB |
1.0.5.4 |
latest linux/jammy R-4.5 | disaggR_1.0.5.4.tar.gz |
880.3 KiB |
1.0.5.4 |
latest linux/noble R-4.5 | disaggR_1.0.5.4.tar.gz |
880.0 KiB |
1.0.5.4 |
latest source/ R- | disaggR_1.0.5.4.tar.gz |
1.1 MiB |
1.0.5.4 |
2026-04-26 source/ R- | disaggR_1.0.5.4.tar.gz |
1.1 MiB |
1.0.5.4 |
2026-04-23 source/ R- | disaggR_1.0.5.4.tar.gz |
1.1 MiB |
1.0.5.4 |
2026-04-09 windows/windows R-4.5 | disaggR_1.0.5.4.zip |
897.3 KiB |
1.0.5.3 |
2025-04-20 source/ R- | disaggR_1.0.5.3.tar.gz |
1.6 MiB |