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Inference and Prediction in Large Dimensions

Denis Bosq (University Paris 6) Delphine Blanke (LSTA)

$178.95

Hardback

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English
JOHN WILEY & SONS
19 October 2007
This 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.

By:   ,
Imprint:   JOHN WILEY & SONS
Country of Publication:   United States
Dimensions:   Height: 234mm,  Width: 158mm,  Spine: 21mm
Weight:   603g
ISBN:   9780470017616
ISBN 10:   0470017619
Series:   Wiley Series in Probability and Statistics
Pages:   336
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active

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.

Reviews for Inference and Prediction in Large Dimensions

This book provides a rigorous and thorough account of modern mathematical statistics as applied to the classic problems of prediction, filtering, inference with kernels, and high-dimensional linear processes ... All in all, Large Sample Techniques in Statistics is an excellent book that I recommend whole-heartedly. (Journal of the American Statistical Association, 1 December 2011)


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