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, n-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-Dud Series co-published between Dud ( www.dud.com ) and John Wiley and Sons, Ltd.
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.