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Some challenges for statistics

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Abstract

The paper gives a highly personal sketch of some current trends in statistical inference. After an account of the challenges that new forms of data bring, there is a brief overview of some topics in stochastic modelling. The paper then turns to sparsity, illustrated using Bayesian wavelet analysis based on a mixture model and metabolite profiling. Modern likelihood methods including higher order approximation and composite likelihood inference are then discussed, followed by some thoughts on statistical education.

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Authors and Affiliations

  1. Institute of Mathematics, School of Basic Sciences, Ecole Polytechnique Fédérale de Lausanne, STAT-IMA-FSB-EPFL, Station 8, 1015, Lausanne, Switzerland

    A. C. Davison

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  1. A. C. Davison
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Correspondence to A. C. Davison.

Additional information

This paper is based on a lecture given at a ceremony to inaugurate the new building of the Department of Statistics at the Università Ca’ Foscari, Venice, in September 2006. Some of the work described was performed in collaborations with Christophe Ancey, Alessandra Brazzale, Gaëlle Messerli, Vahid Partovi Nia, Nancy Reid and Sam Zeeman. The author thanks members of the Venice department for their generous hospitality and Christophe Ancey, Nicola Sartori, Victor Panaretos, Vahid Partovi Nia and referees for their helpful comments. The work was supported by the Swiss National Science Foundation.

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Davison, A.C. Some challenges for statistics. Stat. Meth. & Appl. 17, 167–181 (2008). https://doi.org/10.1007/s10260-007-0079-z

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