Tagebuch des fondamentaux de l'énergie renouvelable et des applications
Libre accès

Abstrait

An Implementation of the Mycielski Algorithm as a Predictor in R

Carsten Croonenbroeck and Daniel Ambach

Univariate time series analysis is usually performed by arbitrarily complex parametric modeling. At least for prediction, a simple non-parametric alternative is the Mycielski algorithm, a forecasting method based on pat- tern matching. The reproducible research presented here shows how to perform out of sample forecasts using the methodology of Mycielski. The algorithm provides well results in scenarios where usual univariate models such as ARIMA family models return limited accuracy. In this article we describe the idea of the Mycielski based prediction algorithm in general. We contribute a reference implementation in R and give a short example.