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disaggR  

Two-Steps Benchmarks for Time Series Disaggregation
View on CRAN: Click here


Download and install disaggR package within the R console
Install from CRAN:
install.packages("disaggR")

Install from Github:
library("remotes")
install_github("cran/disaggR")

Install by package version:
library("remotes")
install_version("disaggR", "1.0.5.4")



Attach the package and use:
library("disaggR")
Maintained by
Pauline Meinzel
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-08-24
Latest Update:
Description:
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 M
How to cite:
Pauline Meinzel (2020). disaggR: Two-Steps Benchmarks for Time Series Disaggregation. R package version 1.0.5.4, https://cran.r-project.org/web/packages/disaggR. Accessed 25 Jun. 2026.
Previous versions and publish date:
0.1.5 (2020-08-24 17:50), 0.1.6 (2020-08-25 16:40), 0.1.7 (2020-10-09 19:10), 0.1.8 (2020-10-10 23:20), 0.1.9 (2020-10-12 01:30), 0.1.11 (2020-12-09 18:20), 0.2.0.2 (2021-04-10 06:20), 0.2.0.3 (2021-04-11 17:20), 0.2.1 (2021-05-03 17:40), 1.0.0 (2021-06-18 15:40), 1.0.1 (2021-07-21 21:50), 1.0.2 (2021-08-23 20:20), 1.0.3.1 (2022-03-04 12:40), 1.0.3 (2022-02-22 08:10), 1.0.4.1 (2022-12-13 22:40), 1.0.5.1 (2023-10-07 21:40), 1.0.5.2 (2024-02-09 14:10), 1.0.5.3 (2024-07-11 10:10), 1.0.5 (2023-02-21 01:10)
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