accuracy.hybridModel

Accuracy measures for hybridModel
objects.

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.

David Shaub

forecastHybrid

Convenient Functions for Ensemble Time Series Forecasts

Peter Ellis

accuracy.hybridModel function

<dl><dt>object</dt>
<dd>the input hybridModel.</dd>
<dt>individual</dt>
<dd>if <code>TRUE</code>, return the accuracy of the component models instead
of the accuracy for the whole ensemble model.</dd>
<dt>...</dt>
<dd>other arguments (ignored).</dd>
<dt>f</dt>
<dd>Deprecated. Please use `object` instead.</dd></dl>

Arguments

Author

Accuracy measures for hybridModel objects — accuracy.hybridModel

<dl>

<dt>object</dt>
<dd>the input hybridModel.</dd>


<dt>individual</dt>
<dd>if <code>TRUE</code>, return the accuracy of the component models instead
of the accuracy for the whole ensemble model.</dd>


<dt>...</dt>
<dd>other arguments (ignored).</dd>


<dt>f</dt>
<dd>Deprecated. Please use `object` instead.</dd>

</dl>

accuracy.hybridModel: Accuracy measures for hybridModel objects

Description

Usage

Value

Arguments

Author

Details

See Also