Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection

Nicolás Jorge Hernández Banadik, Gabriel Martos, Alberto Muñoz García and Javier M. Moguerza

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: 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.

Keywords: Anomaly; detection; Functional; data; Entropy; Stochastic; process; Minimum-entropy; sets (search for similar items in EconPapers)
Date: 2018-05-01
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:26915

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