forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts
Version 0.4.0

Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetam(), nnetar(), stlm(), and tbats() can be combined with equal weights, weights based on in-sample errors, or CV weights. Cross validation for time series data and user-supplied models and forecasting functions is also supported to evaluate model accuracy.

AuthorDavid Shaub [aut, cre], Peter Ellis [aut]
Date of publication2017-03-31 06:12:43 UTC
MaintainerDavid Shaub <davidshaub@gmx.com>
LicenseGPL-3
Version0.4.0
URL https://github.com/ellisp/forecastHybrid
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("forecastHybrid")

Getting started

Using the \"forecastHybrid\" package

Popular man pages

accuracy.default: Generic method for accuracy
cvts: Cross validation for time series
extractForecasts: Extract cross validated rolling forecasts
fitted.hybridModel: Extract Model Fitted Values
forecast.hybridModel: Hybrid forecast
hybridModel: Hybrid time series modelling
tsCombine: Combine multiple sequential time series
See all...

All man pages Function index File listing

Man pages

accuracy: Generic method for accuracy
accuracy.cvts: Accuracy measures for cross-validated time series
accuracy.default: Generic method for accuracy
accuracy.hybridModel: Accuracy measures for hybridModel objects
cvts: Cross validation for time series
extractForecasts: Extract cross validated rolling forecasts
fitted.hybridModel: Extract Model Fitted Values
forecast.hybridModel: Hybrid forecast
forecast.thetam: Forecast using a Theta model
hybridModel: Hybrid time series modelling
is.hybridModel: Test if the object is a hybridModel object
plot.hybridModel: Plot a hybridModel object
plot.thetam: Plot components from Theta model
print.hybridModel: Print information about the hybridModel object
residuals.hybridModel: Extract Model Residuals
summary.hybridModel: Print a summary of the hybridModel object
thetam: Theta method 'model'
tsCombine: Combine multiple sequential time series
tsPartition: Generate training and test indices for time series cross...
tsSubsetWithIndices: Subset time series with provided indices

Functions

Files

inst
inst/NEWS.md
inst/doc
inst/doc/forecastHybrid.html
inst/doc/forecastHybrid.R
inst/doc/forecastHybrid.Rmd
tests
tests/testthat.R
tests/testthat
tests/testthat/test-generics.R
tests/testthat/test-accuracy.r
tests/testthat/test-forecast.hybridModel.R
tests/testthat/test-levels.R
tests/testthat/test-theta.R
tests/testthat/test-cvts.R
tests/testthat/test-hybridModel.R
NAMESPACE
R
R/hybridModel.R
R/theta.R
R/cvts.R
R/helper.R
R/forecast.hybridModel.R
vignettes
vignettes/forecastHybrid.Rmd
MD5
build
build/vignette.rds
DESCRIPTION
man
man/plot.hybridModel.Rd
man/tsCombine.Rd
man/accuracy.cvts.Rd
man/residuals.hybridModel.Rd
man/accuracy.Rd
man/forecast.hybridModel.Rd
man/thetam.Rd
man/accuracy.default.Rd
man/is.hybridModel.Rd
man/extractForecasts.Rd
man/tsPartition.Rd
man/tsSubsetWithIndices.Rd
man/plot.thetam.Rd
man/hybridModel.Rd
man/fitted.hybridModel.Rd
man/print.hybridModel.Rd
man/summary.hybridModel.Rd
man/cvts.Rd
man/forecast.thetam.Rd
man/accuracy.hybridModel.Rd
forecastHybrid documentation built on May 19, 2017, 10:50 a.m.

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