Inference and Prediction in Large Dimensions
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Inference and Prediction in Large Dimensions by Denis Bosq
Book DescriptionThis book offers a predominantly theoretical coverage of statistical prediction, with some potential applications discussed, when data and/ or parameters belong to a large or infinite dimensional space. It develops the theory of statistical prediction, non-parametric estimation by adaptive projection - with applications to tests of fit and prediction, and theory of linear processes in function spaces with applications to prediction of continuous time processes. This work is in the Wiley-Dunod Series co-published between Dunod ( www.dunod.com ) and John Wiley and Sons, Ltd.
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Book DetailsISBN: 9780470017616
(231mm x 158mm x 23mm)
Publisher: John Wiley and Sons Ltd
Publish Date: 19-Oct-2007
Country of Publication: United States
Books By Author Denis Bosq
Mathematical Statistics and Stochastic Processes, Hardback (April 2012)» View all books by Denis Bosq
Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today s practitioners.
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Author Biography - Denis Bosq
Denis Bosq is a Professor at the Laboratory of Theoretical and Applied Statistics, University of Pierre & Marie Curie - Paris 6. He has over 100 published papers, 5 books, and is chief editor of the journal 'Statistical Inference for Stochastic Processes' as well as associate editor for the 'Journal of Non-Parametric Statistics'. He is a well-known specialist in the field of non-parametric statistical inference.
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