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Bayesian Inference on a Cox Process Associated with a Dirichlet Process

by Larissa Valmy, Jean Vaillant
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 18
Year of Publication: 2014
Authors: Larissa Valmy, Jean Vaillant
10.5120/16691-6825

Larissa Valmy, Jean Vaillant . Bayesian Inference on a Cox Process Associated with a Dirichlet Process. International Journal of Computer Applications. 95, 18 ( June 2014), 1-7. DOI=10.5120/16691-6825

@article{ 10.5120/16691-6825,
author = { Larissa Valmy, Jean Vaillant },
title = { Bayesian Inference on a Cox Process Associated with a Dirichlet Process },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 18 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number18/16691-6825/ },
doi = { 10.5120/16691-6825 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:19:44.647581+05:30
%A Larissa Valmy
%A Jean Vaillant
%T Bayesian Inference on a Cox Process Associated with a Dirichlet Process
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 18
%P 1-7
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In ecology and epidemiology, spatio-temporal distributions of events can be described by Cox processes. Situations for which there exists a hidden process which contributes to random effects on the intensity of the observed Cox process are considered. The observed process is a generalized shot noise Cox process and the hidden process is a Poisson process associated with a Dirichlet process. The distributional properties of quadrat counts are presented and bayesian inference is proposed for estimating and predicting parameters of interest in the model. Illustrations are given from weed spatial count data and disease mortality data.

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Index Terms

Computer Science
Information Sciences

Keywords

point process Cox process bayesian inference ecology epidemiology

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