Estimation of entropy for Poisson marked point processes

Patricia Alonso Ruiz, Evgeny Spodarev

Type: Article

Publication Date: 2017-03-01

Citations: 4

DOI: https://doi.org/10.1017/apr.2016.87

Abstract

Abstract In this paper a kernel estimator of the differential entropy of the mark distribution of a homogeneous Poisson marked point process is proposed. The marks have an absolutely continuous distribution on a compact Riemannian manifold without boundary. We investigate L 2 and the almost surely consistency of this estimator as well as its asymptotic normality.

Locations

Advances in Applied Probability - View - PDF
arXiv (Cornell University) - View - PDF

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+	Introduction to Nonparametric Estimation	2008	Alexandre B. Tsybakov
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+	On the asymptotic normality of kernel density estimators for causal linear random fields	2013	Yizao Wang Michael Woodroofe
+ PDF Chat	A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION	1956	M. Rosenblatt
+	Kernel density estimation with spherical data	1987	Peter Hall G. S. Watson Javier Cabrera