generate_proxy_trend_forecasts

Generating proxy trend forecasts from objects of the class "visitation_model".

Performs modeling and forecasting of park visitor counts
using social media data and (partial) on-site visitor counts.
Specifically, the model is built based on an automatic decomposition
of the trend and seasonal components of the social media-based park visitor counts,
from which short-term forecasts of the visitor counts and percent changes
in the visitor counts can be made. A reference for the underlying model that 'VisitorCounts' uses can be found at
Russell Goebel, Austin Schmaltz, Beth Ann Brackett, Spencer A. Wood, Kimihiro Noguchi (2023) <doi:10.1002/for.2965> .

Robert Bowen

VisitorCounts

Modeling and Forecasting Visitor Counts Using Social Media

Russell Goebel

Beth Ann Brackett

Kimihiro Noguchi

Dylan Way

generate_proxy_trend_forecasts function

<dl><dt>object</dt>
<dd>A visitation model object.</dd>
<dt>n_ahead</dt>
<dd>The number of desired forecasts.</dd>
<dt>starttime</dt>
<dd>The start time of the desired forecasts.</dd>
<dt>endtime</dt>
<dd>The end time of the desired forecasts.</dd>
<dt>proxy_trend_correction</dt>
<dd>The lag correction needed on the proxy trend.</dd>
<dt>ts_frequency</dt>
<dd>Frequency of the time series to forecast.</dd></dl>

Arguments

Generate Proxy Trend Forecasts — generate_proxy_trend_forecasts

<dl>

<dt>object</dt>
<dd>A visitation model object.</dd>


<dt>n_ahead</dt>
<dd>The number of desired forecasts.</dd>


<dt>starttime</dt>
<dd>The start time of the desired forecasts.</dd>


<dt>endtime</dt>
<dd>The end time of the desired forecasts.</dd>


<dt>proxy_trend_correction</dt>
<dd>The lag correction needed on the proxy trend.</dd>


<dt>ts_frequency</dt>
<dd>Frequency of the time series to forecast.</dd>

</dl>

generate_proxy_trend_forecasts: Generate Proxy Trend Forecasts

Description

Usage

Value

Arguments