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>).
|Depends:||R (≥ 3.6.0)|
|Imports:||graphics, grDevices, methods, RColorBrewer (≥ 1.1-2), stats, utils|
|Suggests:||knitr, ggplot2 (≥ 3.0.0), rmarkdown (≥ 2.0.0), shiny (≥ 1.5.0), shinytest2 (≥ 0.1.0), testthat (≥ 3.0.0), vdiffr (≥ 1.0.0)|
|Author:||Arnaud Feldmann [aut] (Author, creator and maintener of the package until the version 1.0.2), Franck Arnaud [ctb] (barplot base graphics method for the mts class), Thomas Laurent [cre], Institut national de la statistique et des études économiques [cph] (https://www.insee.fr/)|
|Maintainer:||Thomas Laurent <thomas.laurent at insee.fr>|
|License:||MIT + file LICENSE|
|CRAN checks:||disaggR results|
Introduction to disaggR
Outliers in two-step benchmarks
|Windows binaries:||r-devel: disaggR_1.0.5.zip, r-release: disaggR_1.0.5.zip, r-oldrel: disaggR_1.0.5.zip|
|macOS binaries:||r-release (arm64): disaggR_1.0.5.tgz, r-oldrel (arm64): disaggR_1.0.5.tgz, r-release (x86_64): disaggR_1.0.5.tgz, r-oldrel (x86_64): disaggR_1.0.5.tgz|
|Old sources:||disaggR archive|
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