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Bayesian Inference on a Cox Process Associated with a Dirichlet Process

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 95 - Number 18
Year of Publication: 2014
Larissa Valmy
Jean Vaillant

Larissa Valmy and Jean Vaillant. Article: Bayesian Inference on a Cox Process Associated with a Dirichlet Process. International Journal of Computer Applications 95(18):1-7, June 2014. Full text available. BibTeX

	author = {Larissa Valmy and Jean Vaillant},
	title = {Article: Bayesian Inference on a Cox Process Associated with a Dirichlet Process},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {95},
	number = {18},
	pages = {1-7},
	month = {June},
	note = {Full text available}


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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