Alain Berlinet; Christine Thomas-Agnan Reproducing Kernel Hilbert Spaces in Probability and Statistics 9781461347927

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Автор: Alain Berlinet; Christine Thomas-Agnan
Название: Reproducing Kernel Hilbert Spaces in Probability and Statistics
ISBN: 9781461347927
Издательство: Springer
Классификация:

Экономическая теория и философия

Вероятность и статистика

ISBN-10: 1461347920
Обложка/Формат: Paperback
Страницы: 355
Вес: 0.53 кг.
Дата издания: 22.12.2012
Язык: English
Издание: Softcover reprint of
Иллюстрации: Xxii, 355 p.
Размер: 234 x 156 x 20
Читательская аудитория: Professional & vocational
Основная тема: Economics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: The reproducing kernel Hilbert space construction is a bijection or transform theory which associates a positive definite kernel (gaussian processes) with a Hilbert space offunctions. Like all transform theories (think Fourier), problems in one space may become transparent in the other, and optimal solutions in one space are often usefully optimal in the other. The theory was born in complex function theory, abstracted and then accidently injected into Statistics; Manny Parzen as a graduate student at Berkeley was given a strip of paper containing his qualifying exam problem- It read reproducing kernel Hilbert space- In the 1950s this was a truly obscure topic. Parzen tracked it down and internalized the subject. Soon after, he applied it to problems with the following fla- vor: consider estimating the mean functions of a gaussian process. The mean functions which cannot be distinguished with probability one are precisely the functions in the Hilbert space associated to the covariance kernel of the processes. Parzens own lively account of his work on re- producing kernels is charmingly told in his interview with H. Joseph Newton in Statistical Science, 17, 2002, p. 364-366. Parzen moved to Stanford and his infectious enthusiasm caught Jerry Sacks, Don Ylvisaker and Grace Wahba among others. Sacks and Ylvis- aker applied the ideas to design problems such as the following. Sup- pose (XdO

Reproducing Kernel Hilbert Spaces in Probability and Statistics, Alain Berlinet; Christine Thomas-Agnan