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 |
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 |
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