Entropy 2012, 14(10), 1829-1841; doi:10.3390/e14101829
Article

On Extracting Probability Distribution Information from Time Series

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Received: 15 August 2012; in revised form: 8 September 2012 / Accepted: 21 September 2012 / Published: 28 September 2012
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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.
Keywords: Bandt–Pompe; histograms; time-series
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MDPI and ACS Style

Kowalski, A.M.; Martin, M.T.; Plastino, A.; Judge, G. On Extracting Probability Distribution Information from Time Series. Entropy 2012, 14, 1829-1841.

AMA Style

Kowalski AM, Martin MT, Plastino A, Judge G. On Extracting Probability Distribution Information from Time Series. Entropy. 2012; 14(10):1829-1841.

Chicago/Turabian Style

Kowalski, Andres M.; Martin, Maria Teresa; Plastino, Angelo; Judge, George. 2012. "On Extracting Probability Distribution Information from Time Series." Entropy 14, no. 10: 1829-1841.


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