Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 54, No. 4 (2005), pp. 721-737 (17 pages) The paper discusses the estimation of an unknown population size n. Suppose that ...

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...

The focus of this article is on the nature of the likelihood associated with N-mixture models for repeated count data. It is shown that the infinite sum embedded in the likelihood associated with the ...

Maximum likelihood estimation of the parameters of a statistical model involves maximizing the likelihood or, equivalently, the log likelihood with respect to the parameters. The parameter values at ...