On extracting probability distribution information from time series

Abstract

Time-series (TS) are employed in a variety of academic disciplines. In this paper we focus on extracting probability density functions (PDFs) from TS to gain an insight into the underlying dynamic processes. On discussing this >extraction> problem, we consider two popular approaches that we identify as histograms and Bandt-Pompe. We use an information-theoretic method to objectively compare the information content of the concomitant PDFs. © 2012 by the authors.