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.
|Suggests:||tsbox, testthat, knitr, rmarkdown, covr|
|Author:||Christoph Sax [aut, cre], Peter Steiner [aut], Tommaso Di Fonzo [ctb]|
|Maintainer:||Christoph Sax <christoph.sax at gmail.com>|
|Citation:||tempdisagg citation info|
|CRAN checks:||tempdisagg results|
Temporal Disaggregation to High-Frequency (e.g., to daily)
|Windows binaries:||r-devel: tempdisagg_1.1.zip, r-release: tempdisagg_1.1.zip, r-oldrel: tempdisagg_1.1.zip|
|macOS binaries:||r-release (arm64): tempdisagg_1.1.tgz, r-oldrel (arm64): tempdisagg_1.1.tgz, r-release (x86_64): tempdisagg_1.1.tgz, r-oldrel (x86_64): tempdisagg_1.1.tgz|
|Old sources:||tempdisagg archive|
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