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forecastHybrid (version 4.2.17)

Convenient Functions for Ensemble Time Series Forecasts

Description

Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetaf(), nnetar(), stlm(), tbats(), and snaive() can be combined with equal weights, weights based on in-sample errors (introduced by Bates & Granger (1969) ), or cross-validated weights. Cross validation for time series data with user-supplied models and forecasting functions is also supported to evaluate model accuracy.

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Version

Install

install.packages('forecastHybrid')

Monthly Downloads

3,707

Version

4.2.17

License

GPL-3

Issues

10

Pull Requests

0

Stars

79

Forks

23

Maintainer

David Shaub

Last Published

February 12th, 2019

Functions in forecastHybrid (4.2.17)

fitted.hybridModel

Extract Model Fitted Values
plot.thetam

Plot components from Theta model
prepareTimeseries

Helper function to validate and clean the input time series
accuracy.cvts

Accuracy measures for cross-validated time series
accuracy.hybridModel

Accuracy measures for hybridModel objects
is.hybridModel

Test if the object is a hybridModel object
plot.hybridModel

Plot a hybridModel object
residuals.hybridModel

Extract Model Residuals
cvts

Cross validation for time series
extractForecasts

Extract cross validated rolling forecasts
summary.hybridModel

Print a summary of the hybridModel object
getModelName

Translate character to model name
hybridModel

Hybrid time series modeling
tsCombine

Combine multiple sequential time series
tsPartition

Generate training and test indices for time series cross validation
checkModelArgs

Helper function to test all the model arguments (e.g. a.args, e.args, etc)
checkParallelArguments

Helper function to check the that the parallel arguments are valid
print.hybridModel

Print information about the hybridModel object
forecast.thetam

Forecast using a Theta model
getModel

Return a forecast model function for a given model character
thetam

Theta method 'model'
removeModels

Helper function to remove models that require more data
tsSubsetWithIndices

Subset time series with provided indices
unwrapParallelModels

Helper function used to unpack the fitted model objects from a list
thiefModel

Forecast ensemble using THieF
forecast.hybridModel

Hybrid forecast