Package: forecastHybrid 5.1.21

David Shaub
forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts
Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetaf(), nnetar(), stlm(), tbats(), snaive() and arfima() can be combined with equal weights, weights based on in-sample errors (introduced by Bates & Granger (1969) <doi:10.1057/jors.1969.103>), or cross-validated weights. Cross validation for time series data with user-supplied models and forecasting functions is also supported to evaluate model accuracy.
Authors:
forecastHybrid_5.1.21.tar.gz
forecastHybrid_5.1.21.zip(r-4.7-any)forecastHybrid_5.1.21.zip(r-4.6-any)forecastHybrid_5.1.21.zip(r-4.5-any)
forecastHybrid_5.1.21.tgz(r-4.6-any)forecastHybrid_5.1.21.tgz(r-4.5-any)
forecastHybrid_5.1.21.tar.gz(r-4.7-any)forecastHybrid_5.1.21.tar.gz(r-4.6-any)
forecastHybrid_5.1.21.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
forecastHybrid/json (API)
| # Install 'forecastHybrid' in R: |
| install.packages('forecastHybrid', repos = c('https://ellisp.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ellisp/forecasthybrid/issues
Last updated from:471266726a. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 196 | ||
| source / vignettes | OK | 217 | ||
| linux-release | OK | 161 | ||
| macos-release | OK | 141 | ||
| macos-oldrel | OK | 108 | ||
| windows-devel | OK | 161 | ||
| windows-release | OK | 109 | ||
| windows-oldrel | OK | 152 | ||
| wasm-release | OK | 96 |
Exports:cvtsextractForecastshybridModelis.hybridModelthetamthiefModeltsCombinetsPartitiontsSubsetWithIndices
Dependencies:clicodetoolscolorspacecpp11doParallelfarverforeachforecastfracdiffgenericsggplot2gluegtablehtsisobanditeratorslabelinglatticelifecyclelmtestmagrittrMatrixnlmennetpurrrR6RColorBrewerRcppRcppArmadilloRcppEigenrlangS7scalesSparseMthieftimeDateurcavctrsviridisLitewithrzoo