Two-Steps Benchmarks for Time Series Disaggregation

The twoStepsBenchmark() and threeRuleSmooth() functions allow you to disaggregate a low-frequency time-serie with higher frequency time-series, 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

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.0.2 by Thomas Laurent, 2 months ago

Report a bug at

Browse source code at

Authors: 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] (

Documentation:   PDF Manual  

Task views: Time Series Analysis

MIT + file LICENSE license

Imports graphics, grDevices, methods, RColorBrewer, stats, utils

Suggests knitr, ggplot2, rmarkdown, shiny, shinytest, testthat, vdiffr

See at CRAN