IRF.ARIMA

Calculate impulse responses from a fable model

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

IRF.ARIMA function

<dl><dt>x</dt>
<dd>A fitted model.</dd>
<dt>new_data</dt>
<dd>A tsibble containing the time points and exogenous regressors to produce forecasts for.</dd>
<dt>specials</dt>
<dd>(passed by <code>fabletools::forecast.mdl_df()</code>).</dd>
<dt>...</dt>
<dd>Other arguments passed to methods</dd></dl>

Arguments

Calculate impulse responses from a fable model — IRF.ARIMA

<dl>

<dt>x</dt>
<dd>A fitted model.</dd>


<dt>new_data</dt>
<dd>A tsibble containing the time points and exogenous regressors to produce forecasts for.</dd>


<dt>specials</dt>
<dd>(passed by <code>fabletools::forecast.mdl_df()</code>).</dd>


<dt>...</dt>
<dd>Other arguments passed to methods</dd>

</dl>

IRF.ARIMA: Calculate impulse responses from a fable model

Description

Usage

Arguments