Likelihood Computations for Extended Poisson Process Models
by Heather M. Podlich, Malcolm J. Faddy and Gordon K. Smyth
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.
extended Poisson process models, matrix of transition rates,
expokit, maximum likelihood estimation
Heather M. Podlich
Malcolm J. Faddy,
Gordon K. Smyth,
John P. Hinde
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