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Alain Berlinet - Reproducing Kernel Hilbert Spaces in Probability and Statistics - 9781402076794 - V9781402076794
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Reproducing Kernel Hilbert Spaces in Probability and Statistics

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Description for Reproducing Kernel Hilbert Spaces in Probability and Statistics Hardback. Covers theoretical questions including the extension of the formalism, as well as more practical ones such as computational issues. This book focuses on statistical signal processing, nonparametric curve estimation, random measures, limit theorems, learning theory and some applications at the fringe between Statistics and Approximation Theory. Num Pages: 355 pages, biography. BIC Classification: KC. Category: (G) General (US: Trade); (U) Tertiary Education (US: College). Dimension: 166 x 242 x 28. Weight in Grams: 712.
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 1950's this was a ... Read more

Product Details

Format
Hardback
Publication date
2003
Publisher
Springer-Verlag New York Inc. United States
Number of pages
355
Condition
New
Number of Pages
355
Place of Publication
New York, NY, United States
ISBN
9781402076794
SKU
V9781402076794
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

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