Likelihood Computations for Extended Poisson Process Models

by Heather M. Podlich, Malcolm J. Faddy and Gordon K. Smyth .

Abstract: Some computational aspects of maximum likelihood estimation for extended Poisson process models are discussed, with computation of log-likelihood derivatives being of particular interest. A method is proposed for computation of these derivatives that involves extending the matrix of transition rates describing the underlying stochastic process. This scheme is designed for parametric forms of the transition rates that can include covariate dependence.

Key Words: extended Poisson process models, matrix of transition rates, expokit, maximum likelihood estimation

Authors:
Heather M. Podlich , h.podlich@mailbox.gu.edu.au
Malcolm J. Faddy, m.faddy@math.canterbury.ac.nz
Gordon K. Smyth, gks@maths.uq.edu.au

Editor: John P. Hinde , J.P.Hinde@exeter.ac.uk

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