Publisher description for Reproducing kernel Hilbert spaces in probability and statistics / Alain Berlinet, Christine Thomas-Agnan.


Bibliographic record and links to related information available from the Library of Congress catalog


Information from electronic data provided by the publisher. May be incomplete or contain other coding.


Counter
The book covers theoretical questions including the latest extension of the formalism (therefore of interest to pure mathematicians), as well as more practical ones such as computational issues. It focuses on some of the more fruitful and promising applications, including statistical signal processing, nonparametric curve estimation, random measures, limit theorems, learning theory and some applications at the fringe between Statistics and Approximation Theory. The intention is to put together topics apparently different but sharing the same background. The text is geared to graduate students in Statistics, Mathematics or Engineering, or to scientists with an equivalent level. A lot of examples and applications are given and the book contains a broad variety of exercises so that it can be used as a textbook at a postgraduate level.


Library of Congress subject headings for this publication:
Hilbert space.
Kernel functions.
Probabilities.
Mathematical statistics.