residuals.AR

Provides a collection of commonly used univariate and multivariate
time series forecasting models including automatically selected exponential
smoothing (ETS) and autoregressive integrated moving average (ARIMA) models.
These models work within the 'fable' framework provided by the 'fabletools'
package, which provides the tools to evaluate, visualise, and combine models
in a workflow consistent with the tidyverse.

Mitchell O'Hara-Wild

fable

Forecasting Models for Tidy Time Series

Rob Hyndman

Earo Wang

Gabriel Caceres

Christoph Bergmeir

Tim-Gunnar Hensel

Timothy Hyndman

residuals.AR function

<dl><dt>object</dt>
<dd>The time series model used to produce the forecasts</dd>
<dt>type</dt>
<dd>The type of residuals to extract.</dd>
<dt>...</dt>
<dd>Additional arguments for forecast model methods.</dd></dl>

Arguments

Extract residuals from a fable model — residuals.AR

<dl>

<dt>object</dt>
<dd>The time series model used to produce the forecasts</dd>


<dt>type</dt>
<dd>The type of residuals to extract.</dd>


<dt>...</dt>
<dd>Additional arguments for forecast model methods.</dd>

</dl>

Extract residuals from a fable model

residuals.AR: Extract residuals from a fable model

Description

Usage

Value

Arguments

Examples