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Probabilistic Forecast Combination Using CRPS Learning • profoc

Probabilistic Forecast Combination Using CRPS Learning • profoc

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AEO Score: 5/10

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In the Engagemii AEO index

profoc.berrisch.biz

About Probabilistic Forecast Combination Using CRPS Learning • profoc

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>.

Key Topics

The profoc Package

Details

Category: Technology

profoc.berrisch.biz

AI Visibility Breakdown

1

Structured Data

8

Content Structure

5

Entity Clarity

3

E-E-A-T Signals

8

Technical AEO

5

AI Discoverability

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Scored by Engagemii on May 29, 2026. Methodology: engagemii.com/aeo/methodology

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