CRAN/E | disaggR

disaggR

Two-Steps Benchmarks for Time Series Disaggregation

Installation

About

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, ).

inseefr.github.io/disaggR/
Bug report File report

Key Metrics

Version 1.0.5.2
R ≥ 3.6.0
Published 2024-02-09 76 days ago
Needs compilation? no
License MIT
License File
CRAN checks disaggR results

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Maintainer

Maintainer

Pauline Meinzel

pauline.meinzel@insee.fr

Authors

Arnaud Feldmann

aut

(Creator and maintener of the package until the version 1.0.2)

Franck Arnaud

ctb

(barplot base graphics method for the mts class)

Pauline Meinzel

cre

Institut national de la statistique et des études économiques

cph

(https://www.insee.fr/)

Material

README
NEWS
Reference manual
Package source

In Views

TimeSeries

Vignettes

Introduction to disaggR
Outliers in two-step benchmarks

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

disaggR archive

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