A sequential reduction method for inference in generalized linear mixed models

6 Dec 2013Helen Ogden

The likelihood for the parameters of a generalized linear mixed model involves an integral which may be of very high dimension. Because of this intractability, many approximations to the likelihood have been proposed, but all can fail when the model is sparse, in that there is only a small amount of information available on each random effect... (read more)

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