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Inference and Prediction in Large Dimensions
Bosq, Denis; Blanke, Delphine
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Description for Inference and Prediction in Large Dimensions
Inference and Prediction in Large Dimensions 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. Series: Wiley Series in Probability and Statistics. Num Pages: 336 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 233 x 161 x 23. Weight in Grams: 658.
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 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.
Product Details
Publication date
2007
Publisher
John Wiley and Sons Ltd United States
Number of pages
336
Condition
New
Series
Wiley Series in Probability and Statistics
Number of Pages
336
Format
Hardback
Place of Publication
, United States
ISBN
9780470017616
SKU
V9780470017616
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Bosq, Denis; Blanke, Delphine
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 ... Read more
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)