predict.boiwsa

S3 method for 'boiwsa' class. Returns forecasts and other information using a combination of nonseasonal
auto.arima and estimates from boiwsa.

Perform seasonal adjustment and forecasting of weekly data.
The package provides a user-friendly interface for computing seasonally
adjusted estimates and forecasts of weekly time series and includes
functions for the construction of country-specific prior adjustment
variables, as well as diagnostic tools to assess the quality of the
adjustments. The methodology is described in more detail in
Ginker (2024) <doi:10.13140/RG.2.2.12221.44000>.

Tim Ginker

boiwsa

Seasonal Adjustment of Weekly Data

Jon Lachman

predict.boiwsa function

<dl><dt>object</dt>
<dd>An object of class <code>boiwsa</code>.</dd>
<dt>...</dt>
<dd>Additional arguments:<ul>
<li><code>n.ahead</code>: Number of periods for forecasting (required).</li>
<li><code>level</code>: Confidence level for prediction intervals. By default is set to c(80, 95).</li>
<li><code>new_H</code>: Matrix with future holiday- and trading day factors.</li>
<li><code>arima.options</code>: List of <code>forecast::Arima</code> arguments for custom modeling.</li>
</ul></dd></dl>

Arguments

Predict — predict.boiwsa

<dl>

<dt>object</dt>
<dd>An object of class <code>boiwsa</code>.</dd>


<dt>...</dt>
<dd>Additional arguments:<ul>
<li><code>n.ahead</code>: Number of periods for forecasting (required).</li>
<li><code>level</code>: Confidence level for prediction intervals. By default is set to c(80, 95).</li>
<li><code>new_H</code>: Matrix with future holiday- and trading day factors.</li>
<li><code>arima.options</code>: List of <code>forecast::Arima</code> arguments for custom modeling.</li>
</ul></dd>

</dl>

predict.boiwsa: Predict

Description

Usage

Value

Arguments