summary.online

Calculates parameters chosen during optimization and aggregates losses.

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

summary.online function

<dl><dt>object</dt>
<dd>Object of class inheriting from 'online'</dd>
<dt>...</dt>
<dd>further arguments are ignored</dd></dl>

Arguments

Summary method for online models — summary.online

<dl>

<dt>object</dt>
<dd>Object of class inheriting from 'online'</dd>


<dt>...</dt>
<dd>further arguments are ignored</dd>

</dl>

summary.online: Summary method for online models

Description

Usage

Arguments