Two-Steps Benchmarks for Time Series Disaggregation

The twoStepsBenchmark() and threeRuleSmooth() functions allow you to disaggregate a low-frequency time-serie with time-series of higher frequency, using the French National Accounts methodology. The aggregated sum of the resulting time-serie is strictly equal to the low-frequency serie within the benchmarking window. Typically, the low-frequency serie is an annual one, unknown for the last year, and the high frequency one is either quarterly or mensual. See "Methodology of quarterly national accounts", Insee Méthodes N°126, by Insee (2012, ISBN:978-2-11-068613-8).


Reference manual

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0.2.1 by Arnaud Feldmann, 14 days ago

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Authors: Arnaud Feldmann [aut, cre] , Franck Arnaud [ctb] (barplot base graphics method for the mts class) , Institut national de la statistique et des études économiques [cph] (

Documentation:   PDF Manual  

Task views: Time Series Analysis

MIT + file LICENSE license

Imports ggplot2, rmarkdown, scales, shiny

Depends on methods

Suggests shinytest, testthat, vdiffr

See at CRAN