Shannon entropy estimation for linear processes

In this paper, we estimate the Shannon entropy S(f)=-E[log(f(x))] of a one-sided linear process with probability density function f(x). We employ the integral estimator Sn(f), which utilizes the standard kernel density estimator fn(x) of f(x). We show that Sn(f) converges to S(f) almost surely and in ¡2 under reasonable conditions.

MoreLess

Year of publication:	2020
Authors:	Fortune, Timothy ; Sang, Hailin
Published in:	Journal of Risk and Financial Management. - Basel : MDPI, ISSN 1911-8074. - Vol. 13.2020, 9, p. 1-13
Publisher:	Basel : MDPI
Subject:	kernel entropy estimation \| linear process \| Shannon entropy

More details

Type of publication:	Article
Type of publication (narrower categories):	Article
Language:	English
Other identifiers:	10.3390/jrfm13090205 [DOI] 1742841511 [GVK] hdl:10419/239289 [Handle]
Source:	EconStor

Persistent link: https://www.econbiz.de/10012611430