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Licensed Unlicensed Requires Authentication Published by De Gruyter August 30, 2008

Approximately Sufficient Statistics and Bayesian Computation

  • Paul Joyce and Paul Marjoram

The analysis of high-dimensional data sets is often forced to rely upon well-chosen summary statistics. A systematic approach to choosing such statistics, which is based upon a sound theoretical framework, is currently lacking. In this paper we develop a sequential scheme for scoring statistics according to whether their inclusion in the analysis will substantially improve the quality of inference. Our method can be applied to high-dimensional data sets for which exact likelihood equations are not possible. We illustrate the potential of our approach with a series of examples drawn from genetics. In summary, in a context in which well-chosen summary statistics are of high importance, we attempt to put the `well' into `chosen.'

Published Online: 2008-8-30

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston

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