onlineforecast: Forecast Modelling for Online Applications

A framework for fitting adaptive forecasting models. Provides a way to use forecasts as input to models, e.g. weather forecasts for energy related forecasting. The models can be fitted recursively and can easily be setup for updating parameters when new data arrives. See the included vignettes, the website <https://onlineforecasting.org> and the paper "onlineforecast: An R package for adaptive and recursive forecasting" <https://journal.r-project.org/articles/RJ-2023-031/>.

Version:	1.0.2
Depends:	R (≥ 3.0.0)
Imports:	Rcpp (≥ 0.12.18), R6 (≥ 2.2.2), splines (≥ 3.1.1), pbs, digest
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, rmarkdown, R.rsp, testthat (≥ 3.0.0), data.table, plotly
Published:	2023-10-12
DOI:	10.32614/CRAN.package.onlineforecast
Author:	Peder Bacher [cre], Hjorleifur G Bergsteinsson [aut]
Maintainer:	Peder Bacher <pbac at dtu.dk>
BugReports:	https://lab.compute.dtu.dk/packages/onlineforecast/-/issues
License:	GPL-3
URL:	https://onlineforecasting.org
NeedsCompilation:	yes
Citation:	onlineforecast citation info
In views:	TimeSeries
CRAN checks:	onlineforecast results

Documentation:

Reference manual:	onlineforecast.pdf
Vignettes:	Forecast evaluation Model selection Setup and use onlineforecast models Setup of data for an onlineforecast model

Downloads:

Package source:	onlineforecast_1.0.2.tar.gz
Windows binaries:	r-devel: onlineforecast_1.0.2.zip, r-release: onlineforecast_1.0.2.zip, r-oldrel: onlineforecast_1.0.2.zip
macOS binaries:	r-release (arm64): onlineforecast_1.0.2.tgz, r-oldrel (arm64): onlineforecast_1.0.2.tgz, r-release (x86_64): onlineforecast_1.0.2.tgz, r-oldrel (x86_64): onlineforecast_1.0.2.tgz
Old sources:	onlineforecast archive

Linking:

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