Asymptotic Normality of the Posterior Distribution for Exponential Models
نویسندگان
چکیده
منابع مشابه
Asymptotic normality of posterior distributions for generalized linear mixed models
Generalized linear mixed models (GLMMs) are widely used in the analysis of non Gaussian repeated measurements such as clustered proportion and count data. The most commonly used approach for inference in these models is based on the Bayesian methods and Markov chain Monte Carlo (MCMC) sampling. However, the validity of Bayesian inferences can be seriously affected by the assumed model for the r...
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Exponential families arise naturally in statistical modelling and the maximum likelihood estimate (MLE) is consistent and asymptotically normal for these models [Berk [2]]. In practice, often one needs to consider models with a large number of parameters, particularly if the sample size is large; see Huber [14], Haberman [13] and Portnoy [18 21]. One may also think that the true model can only ...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1975
ISSN: 0090-5364
DOI: 10.1214/aos/1176343011