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rjd3bench

Overview

The package rjd3bench provides a variety of methods for temporal disaggregation, interpolation, benchmarking, reconciliation and calendarization, using highly efficient algorithms.

Temporal disaggregation & interpolation:

• Chow-Lin, Fernandez and Litterman
• Model-Based Denton
• Autoregressive Distributed Lag (ADL) models
• Reverse regression

Benchmarking:

• Denton
• GRP (Growth Rate Preservation)
• Cubic Splines
• Cholette

Reconciliation and multivariate temporal disaggregation:

• Multivariate Cholette

Calendarization

Installation

Running rjd3 packages requires Java 21 or higher. How to set up such a configuration in R is explained here

Latest release

To get the current stable version (from the latest release):

• From CRAN:

install.packages("rjd3bench")

• From GitHub:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@*release")
remotes::install_github("rjdverse/rjd3bench@*release", build_vignettes = TRUE)

• From r-universe:

install.packages("rjd3bench", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

Development version

To get the current development version from GitHub:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3bench", build_vignettes = TRUE)

Package Maintenance and contributing

Any contribution is welcome and should be done through pull requests and/or issues. pull requests should include updated tests and updated documentation. If functionality is changed, docstrings should be added or updated.

Licensing

The code of this project is licensed under the European Union Public Licence (EUPL).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.