Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
This paper presents an EM algorithm for semiparametric likelihood analysis of linear, generalized linear, and nonlinear regression models with measurement errors in explanatory variables. A structural ...
In this paper, we introduce the class of the nonlinear overdispersed models and derive general formulae for the biases of the maximum likelihood estimators of the parameters in these models, thus ...
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