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tempdisagg: Methods for Temporal Disaggregation and Interpolation of Time Series

Temporal disaggregation methods are used to disaggregate or interpolate a low frequency time series to a higher frequency series, where either the sum, the average, 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. Supports most R time series classes.

Installation

To install or update from from CRAN, run:

install.packages("tempdisagg")

To install the development version:

# install.packages("pak")
pak::pak("cynkra/tempdisagg")

Our article on temporal disaggregation of time series in the R-Journal describes the package and the theory of temporal disaggregation in more detail.

Please report bugs on Github. Thank you!

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Version

Install

install.packages('tempdisagg')

Monthly Downloads

2,754

Version

1.2.0

License

GPL-3

Maintainer

Christoph Sax

Last Published

November 5th, 2025

Functions in tempdisagg (1.2.0)

ta

Temporal Aggregation of Time Series
tempdisagg-package

Methods for Temporal Disaggregation and Interpolation of Time Series
plot.td

Residual Plot for Temporal Disaggregation
gdp.q

Gross Domestic Product
spi.d

SPI Swiss Performance Index
predict.td

Predict Method for Temporal Disaggregation
summary.td

Summary of a Temporal Disaggregation
td

Temporal Disaggregation of Time Series
exports.m

Trade and Sales of Chemical and Pharmaceutical Industry