disaggR: Two-Steps Benchmarks for Time Series Disaggregation

The twoStepsBenchmark() function and its wrappers 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 is either quarterly or mensual. See "Methodology of quarterly national accounts", Insee Méthodes N°126, by Insee (2012, ISBN:978-2-11-068613-8).

Version: 0.1.11
Depends: R (≥ 2.10)
Imports: ggplot2, Rcpp
LinkingTo: Rcpp
Suggests: testthat (≥ 2.1.0), vdiffr
Published: 2020-12-09
Author: Arnaud Feldmann [aut, cre], Institut national de la statistique et des études économiques [cph] (https://www.insee.fr/)
Maintainer: Arnaud Feldmann <arnaud.feldmann at insee.fr>
BugReports: https://github.com/InseeFr/disaggR/issues
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README NEWS
In views: TimeSeries
CRAN checks: disaggR results


Reference manual: disaggR.pdf
Package source: disaggR_0.1.11.tar.gz
Windows binaries: r-devel: disaggR_0.1.11.zip, r-release: disaggR_0.1.11.zip, r-oldrel: disaggR_0.1.11.zip
macOS binaries: r-release: disaggR_0.1.11.tgz, r-oldrel: disaggR_0.1.11.tgz
Old sources: disaggR archive


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