An Implementation of the Mycielski Algorithm as a Predictor in R
- Corresponding Author:
- Carsten Croonenbroeck
Department of Environmental Science
University of Rostock, Justus-von-Liebig-Weg 2
18059 Rostock, Germany
E-mail: [email protected]
Received date: October 13, 2015; Accepted date: December 02, 2015; Published date: December 04, 2015
Citation: Croonenbroeck C, Ambach D (2015) An Implementation of the Mycielski Algorithm as a Predictor in R. J Fundam Renewable Energy Appl 6:195. doi:10.4172/2090-4541.1000195
Copyright: © 2015 Croonenbroeck C, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.