tempdisagg: Methods for Temporal Disaggregation and Interpolation of Time Series

Temporal disaggregation methods are used to disaggregate and interpolate a low frequency time series to a higher frequency series, where either the sum, the mean, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. Contains the methods of Chow-Lin, Santos-Silva-Cardoso, Fernandez, Litterman, Denton and Denton-Cholette, summarized in Sax and Steiner (2013) <doi:10.32614/RJ-2013-028>. Supports most R time series classes.

Version: 1.0
Suggests: tsbox, testthat, knitr, rmarkdown
Published: 2020-02-07
Author: Christoph Sax ORCID iD [aut, cre], Peter Steiner [aut], Tommaso Di Fonzo [ctb]
Maintainer: Christoph Sax <christoph.sax at gmail.com>
BugReports: https://github.com/christophsax/tempdisagg
License: GPL-3
URL: https://journal.r-project.org/archive/2013-2/sax-steiner.pdf
NeedsCompilation: no
Citation: tempdisagg citation info
Materials: README NEWS
In views: TimeSeries
CRAN checks: tempdisagg results

Downloads:

Reference manual: tempdisagg.pdf
Vignettes: Temporal Disaggregation to High-Frequency (e.g., to daily)
Introduction
Package source: tempdisagg_1.0.tar.gz
Windows binaries: r-devel: tempdisagg_1.0.zip, r-devel-gcc8: tempdisagg_0.25.0.zip, r-release: tempdisagg_1.0.zip, r-oldrel: tempdisagg_1.0.zip
OS X binaries: r-release: tempdisagg_1.0.tgz, r-oldrel: tempdisagg_1.0.tgz
Old sources: tempdisagg archive

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