tidy.online.forecaster_loss

<code>tidy</code> will transform the `forecaster_loss`` array of an online object
into a tibble that is better suited for plotting and analysis.

Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) <doi:10.48550/arXiv.2102.00968> <doi:10.1016/j.jeconom.2021.11.008>. The package implements multiple online learning algorithms like Bernstein online aggregation; see Wintenberger (2014) <doi:10.48550/arXiv.1404.1356>. Quantile regression is also implemented for comparison purposes. Model parameters can be tuned automatically with respect to the loss of the forecast combination. Methods like predict(), update(), plot() and print() are available for convenience. This package utilizes the optim C++ library for numeric optimization <https://github.com/kthohr/optim>.

Jonathan Berrisch

profoc

Probabilistic Forecast Combination Using CRPS Learning

Florian Ziel

tidy.online.forecaster_loss function

<dl><dt>x</dt>
<dd>The forecaster_loss of an <code>online</code> object.</dd>
<dt>...</dt>
<dd>Not currently used.</dd></dl>

Arguments

Tidy the Experts' losses of an Online object — tidy.online.forecaster_loss

<dl>

<dt>x</dt>
<dd>The forecaster_loss of an <code>online</code> object.</dd>


<dt>...</dt>
<dd>Not currently used.</dd>

</dl>

tidy.online.forecaster_loss: Tidy the Experts' losses of an Online object

Description

Usage

Value

Arguments