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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>).
Getting started
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Package details |
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| Author | Arnaud Feldmann [aut] (<https://orcid.org/0000-0003-0109-7505>, Author and maintener of the package until the version 1.0.1), Pauline Meinzel [cre], Thomas Laurent [ctb] (Maintener of the package from 1.0.2 to 1.0.5.2), Franck Arnaud [ctb] (barplot base graphics method for the mts class), Institut national de la statistique et des études économiques [cph] (https://www.insee.fr/) |
| Maintainer | Pauline Meinzel <pauline.meinzel@insee.fr> |
| License | MIT + file LICENSE |
| Version | 1.0.5.3 |
| URL | https://inseefr.github.io/disaggR/ |
| Package repository | View on CRAN |
| Installation |
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