Entropy measures for stochastic processes with applications in functional anomaly detection
We propose a definition of entropy for stochastic processes. We provide a reproducing kernel Hilbert space model to estimate entropy from a random sample of realizations of a stochastic process, namely functional data, and introduce two approaches to estimate minimum entropy sets. These sets are rel...
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Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_10994300_v20_n1_p_Martos |
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todo:paper_10994300_v20_n1_p_Martos2023-10-03T16:06:34Z Entropy measures for stochastic processes with applications in functional anomaly detection Martos, G. Hernández, N. Muñoz, A. Moguerza, J.M. Anomaly detection Entropy Functional data Minimum-entropy sets Stochastic process We propose a definition of entropy for stochastic processes. We provide a reproducing kernel Hilbert space model to estimate entropy from a random sample of realizations of a stochastic process, namely functional data, and introduce two approaches to estimate minimum entropy sets. These sets are relevant to detect anomalous or outlier functional data. A numerical experiment illustrates the performance of the proposed method; in addition, we conduct an analysis of mortality rate curves as an interesting application in a real-data context to explore functional anomaly detection. © 2018 by the authors. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_10994300_v20_n1_p_Martos |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
topic |
Anomaly detection Entropy Functional data Minimum-entropy sets Stochastic process |
spellingShingle |
Anomaly detection Entropy Functional data Minimum-entropy sets Stochastic process Martos, G. Hernández, N. Muñoz, A. Moguerza, J.M. Entropy measures for stochastic processes with applications in functional anomaly detection |
topic_facet |
Anomaly detection Entropy Functional data Minimum-entropy sets Stochastic process |
description |
We propose a definition of entropy for stochastic processes. We provide a reproducing kernel Hilbert space model to estimate entropy from a random sample of realizations of a stochastic process, namely functional data, and introduce two approaches to estimate minimum entropy sets. These sets are relevant to detect anomalous or outlier functional data. A numerical experiment illustrates the performance of the proposed method; in addition, we conduct an analysis of mortality rate curves as an interesting application in a real-data context to explore functional anomaly detection. © 2018 by the authors. |
format |
JOUR |
author |
Martos, G. Hernández, N. Muñoz, A. Moguerza, J.M. |
author_facet |
Martos, G. Hernández, N. Muñoz, A. Moguerza, J.M. |
author_sort |
Martos, G. |
title |
Entropy measures for stochastic processes with applications in functional anomaly detection |
title_short |
Entropy measures for stochastic processes with applications in functional anomaly detection |
title_full |
Entropy measures for stochastic processes with applications in functional anomaly detection |
title_fullStr |
Entropy measures for stochastic processes with applications in functional anomaly detection |
title_full_unstemmed |
Entropy measures for stochastic processes with applications in functional anomaly detection |
title_sort |
entropy measures for stochastic processes with applications in functional anomaly detection |
url |
http://hdl.handle.net/20.500.12110/paper_10994300_v20_n1_p_Martos |
work_keys_str_mv |
AT martosg entropymeasuresforstochasticprocesseswithapplicationsinfunctionalanomalydetection AT hernandezn entropymeasuresforstochasticprocesseswithapplicationsinfunctionalanomalydetection AT munoza entropymeasuresforstochasticprocesseswithapplicationsinfunctionalanomalydetection AT moguerzajm entropymeasuresforstochasticprocesseswithapplicationsinfunctionalanomalydetection |
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1782027777517551616 |