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Centre for Statistical & Survey Methodology Working Paper Series
Publication Date
2010
Recommended Citation
Hall, P.; Pham, T.; Wand, M.; and Wang, S.S.J., Asymptotic normality and valid inference for Gaussian variational approximation, Centre for Statistical and Survey Methodology, University of Wollongong, Working Paper 04-10, 2010, 24p.
https://ro.uow.edu.au/cssmwp/55
Abstract
We derive the precise asymptotic distributional behavior of Gaussian variational approximate estimators of the parameters in a singlepredictor Poisson mixed model. These results are the deepest yet obtained concerning the statistical properties of a variational approximation method. Moreover, they give rise to asymptotically valid statistical inference. A simulation study demonstrates that Gaussian variational approximate confidence intervals possess good to excellent coverage properties, and with precision similar to their exact likelihood counterparts.