On extracting probability distribution information from time series

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 w...

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Autores principales: Kowalski, Andrés Mauricio, Martín, María Teresa, Plastino, Ángel Luis, Judge, George
Formato: Articulo
Lenguaje:Inglés
Publicado: 2012
Materias:
Ciencias Exactas
Bandt-pompe
Histograms
Time-series
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/83631
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-83631
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Exactas
Bandt-pompe
Histograms
Time-series
spellingShingle Ciencias Exactas
Bandt-pompe
Histograms
Time-series
Kowalski, Andrés Mauricio
Martín, María Teresa
Plastino, Ángel Luis
Judge, George
On extracting probability distribution information from time series
topic_facet Ciencias Exactas
Bandt-pompe
Histograms
Time-series
description 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.
format Articulo
Articulo
author Kowalski, Andrés Mauricio
Martín, María Teresa
Plastino, Ángel Luis
Judge, George
author_facet Kowalski, Andrés Mauricio
Martín, María Teresa
Plastino, Ángel Luis
Judge, George
author_sort Kowalski, Andrés Mauricio
title On extracting probability distribution information from time series
title_short On extracting probability distribution information from time series
title_full On extracting probability distribution information from time series
title_fullStr On extracting probability distribution information from time series
title_full_unstemmed On extracting probability distribution information from time series
title_sort on extracting probability distribution information from time series
publishDate 2012
url http://sedici.unlp.edu.ar/handle/10915/83631
work_keys_str_mv AT kowalskiandresmauricio onextractingprobabilitydistributioninformationfromtimeseries
AT martinmariateresa onextractingprobabilitydistributioninformationfromtimeseries
AT plastinoangelluis onextractingprobabilitydistributioninformationfromtimeseries
AT judgegeorge onextractingprobabilitydistributioninformationfromtimeseries
bdutipo_str Repositorios
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