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Theory of Gaussian variational approximation for a Poisson mixed model

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posted on 2024-11-16, 08:04 authored by Peter Hall, John Ormerod, Matthew Wand
Likelihood-based inference for the parameters of generalized linear mixed models is hindered by the presence of intractable integrals. Gaussian variational approximation provides a fast and effective means of approximate inference. We provide some theory for this type of approximation for a simple Poisson mixed model. In particular, we establish consistency at rate m−1/2 +n−1, where m is the number of groups and n is the number of repeated measurements.

Funding

Generalised Linear Mixed Models: Theory, Methods and New Areas of Application

Australian Research Council

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History

Citation

Hall, P., Ormerod, J. T. & Wand, M. P. (2011). Theory of Gaussian variational approximation for a Poisson mixed model. Statistica Sinica, 21 (1), 369-389.

Journal title

Statistica Sinica

Volume

21

Issue

1

Pagination

369-389

Language

English

RIS ID

34913

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