Estimation of the intensity function of an inhomogeneous Poisson process with a change-point
RIS ID
137397
Abstract
Recent work on point processes includes studying posterior convergence rates of estimating a continuous intensity function. In this article, convergence rates for estimating the intensity function and change-point are derived for the more general case of a piecewise continuous intensity function. We study the problem of estimating the intensity function of an inhomogeneous Poisson process with a change-point using non-parametric Bayesian methods. An Markov Chain Monte Carlo (MCMC) algorithm is proposed to obtain estimates of the intensity function and the change-point which is illustrated using simulation studies and applications.
Publication Details
Ng, T. Lok J. & Murphy, T. B. (2019). Estimation of the intensity function of an inhomogeneous Poisson process with a change-point. Canadian Journal of Statistics, 47 (4), 604-618.