#131 Get pdf: Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics)

By Evarist Giné, Richard Nickl



Mathematical Foundations of Infinite-Dimensional Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics) By Evarist Giné, Richard Nickl

 |  2016-01-31  |  2016-03-31 | File size: 55.Mb
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Most Helpful In nonparametric and high dimensional statistical models the classical Gauss Fisher Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply and new foundations and ideas have been developed in the past several decades This book gives a coherent account of the statistical theory in infinite dimensional parameter spaces The mathematical foundations include self contained mini courses on the theory of Gaussian a Advance praise Finally a book that goes all the way in the mathematics of nonparametric statistics It is reasonably self contained despite its depth and breadth including accessible overviews of the necessary analysis and approximation theory Aad van

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