window_function_fit_impl

internal

The time series forecasting framework for use with the 'tidymodels' ecosystem.
Models include ARIMA, Exponential Smoothing, and additional time series models
from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition"
(<https://otexts.com/fpp2/>).
Refer to "Prophet: forecasting at scale"
(<https://research.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).

Matt Dancho

modeltime

The Tidymodels Extension for Time Series Modeling

Business Science 

window_function_fit_impl function

<dl><dt>x</dt>
<dd>A dataframe of xreg (exogenous regressors)</dd>
<dt>y</dt>
<dd>A numeric vector of values to fit</dd>
<dt>id</dt>
<dd>An optional ID feature to identify different time series. Should be a quoted name.</dd>
<dt>window_size</dt>
<dd>The period to apply the window function to</dd>
<dt>window_function</dt>
<dd>A function to apply to the window. The default is <code><a href="/link/mean()?package=modeltime&version=1.3.2" data-mini-rdoc="modeltime::mean()">mean()</a></code>.</dd>
<dt>...</dt>
<dd>Additional arguments for the <code>window_function</code>. For example, it's
common to pass <code>na.rm = TRUE</code> for the mean forecast.</dd></dl>

Arguments

Low-Level Window Forecast — window_function_fit_impl

<dl>

<dt>x</dt>
<dd>A dataframe of xreg (exogenous regressors)</dd>


<dt>y</dt>
<dd>A numeric vector of values to fit</dd>


<dt>id</dt>
<dd>An optional ID feature to identify different time series. Should be a quoted name.</dd>


<dt>window_size</dt>
<dd>The period to apply the window function to</dd>


<dt>window_function</dt>
<dd>A function to apply to the window. The default is <code><a href='https://rdrr.io/r/base/mean.html'>mean()</a></code>.</dd>


<dt>...</dt>
<dd>Additional arguments for the <code>window_function</code>. For example, it's
common to pass <code>na.rm = TRUE</code> for the mean forecast.</dd>

</dl>

window_function_fit_impl: Low-Level Window Forecast

Description

Usage

Arguments