Research

CRPS Learning, 2021, Jonathan Berrisch & Florian Ziel

This paper treats how online learning algorithms can be used for the pointwise combination of probabilistic forecasts.

Pre-Print

Presentation

Presentation for the International Symposium on Forecasting (Short)

Modeling and probabilistic forecasting of natural gas prices, 2021, Jonathan Berrisch & Florian Ziel

This paper presents price forecasting studies for two essential European natural-gas products.

Pre-Print

Projects

profoc - An R Package for Probabilistic Forecast Combination

This package implements methods which are proposed and discussed in CRPS Learning.

GitHub

Documentation

sstudentt - A python package implementing the skewed-student-t distribution

This package implements the skewed student-t distribution in python. Parameterized as described in Wurtz et. al (2006) [1]. An implementation in R is already existent [2].

Github

PyPi

Documentation

Development

I develop most of my projects in a docker container that is publicly available for reuse and inspiration. This container makes it easy to reproduce results or develop projects like the profoc R package.

The most convenient way to start is using VS-Code. You can find instructions in the GitHub Repo. However, the bare-bone Docker Container is also available and sufficient.

The Repository is available on GitHub.

The docker container is also available on GitHub

References

.. [1] Wurtz, Y. Chalabi, and L. Luksan. Parameter estimation of arma models with garch/aparch errors. an r and splus software implementation. Journal of Statistical Software, 2006.

.. [2] R Implementation: https://www.gamlss.com/wp-content/uploads/2018/01/DistributionsForModellingLocationScaleandShape.pdf