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 "Short-term heat load forecasting for single family houses" <doi:10.1016/j.enbuild.2013.04.022>.

Version: 0.9.3
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 (≥ 2.1.0), data.table, plotly
Published: 2020-09-15
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
CRAN checks: onlineforecast results

Downloads:

Reference manual: onlineforecast.pdf
Vignettes: Forecast evaluation
Setup and use onlineforecast models
Setup of data for an onlineforecast model
Package source: onlineforecast_0.9.3.tar.gz
Windows binaries: r-devel: onlineforecast_0.9.3.zip, r-release: onlineforecast_0.9.3.zip, r-oldrel: onlineforecast_0.9.3.zip
macOS binaries: r-release: onlineforecast_0.9.3.tgz, r-oldrel: onlineforecast_0.9.3.tgz

Linking:

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