Browsing 01 Mathematical Sciences by Author "Ormerod J."

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Browsing 01 Mathematical Sciences by Author "Ormerod J."

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  • Explaining variational approximations 
    Ormerod J.; Wand Matt (American Statistical Association, 2010)
    Variational approximations facilitate approximate inference for the parameters in complex statistical models and provide fast, deterministic alternatives to Monte Carlo methods. However, much of the contemporary literature ...
  • Gaussian variational approximate inference for generalized linear mixed models 
    Ormerod J.; Wand Matthew (American Statistical Association, 2011)
    Variational approximation methods have become a mainstay of contemporary machine learning methodology, but currently have little presence in statistics. We devise an effective variational approximation strategy for fitting ...
  • Mean field variational Bayes for elaborate distributions 
    Wand Matthew; Ormerod J.; Padoan S.; Fruhwirth R. (International Society for Bayesian Analysis, 2011)
    We develop strategies for mean eld variational Bayes approximate inference for Bayesian hierarchical models containing elaborate distributions. We loosely de ne elaborate distributions to be those having more complicated ...
  • On semiparametric regression with O'Sullivan penalised splines 
    Wand Matt; Ormerod J. (Blackwell Publishing Ltd, 2008)
    An exposition on the use of O'Sullivan penalized splines in contemporary semiparametric regression, including mixed model and Bayesian formulations, is presented. O'Sullivan penalized splines are similar to P-splines, but ...
  • Variational Bayesian inference for parametric and nonparametric regression with missing data 
    Faes C.; Ormerod J.; Wand Matthew (American Statistical Association, 2011)
    Bayesian hierarchical models are attractive structures for conducting regression analyses when the data are subject to missingness. However, the requisite probability calculus is challenging and Monte Carlo methods typically ...