ISSN: 2090-4541
+44 1300 500008
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.