Likelihood-based inference for complex data structures

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• Nancy Reid (Toronto)
• Tuesday 05 May 2009, 17:00-18:00
• Wolfson Room (MR 2) Centre for Mathematical Sciences, Wilberforce Road, Cambridge.

If you have a question about this talk, please contact Helen Innes.

Statistical inference based on the likelihood function is well-established as the method of choice for a wide range of applications. As the structure of available data becomes increasingly complex, for example due to intricate sampling schemes, or the measurement of an extremely large number of variables, new developments in likelihood inference are needed. I will discuss some aspects of the current research in adapting likelihood inference to these settings, with particular reference to specific application areas.

This talk is part of the Kuwait Foundation Lectures series.

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