Titlebook: Reproducing Kernel Hilbert Spaces in Probability and Statistics; Alain Berlinet,Christine Thomas-Agnan Book 2004 Springer Science+Business

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Measures and Random Measures,e, has become one of the major fields in Pure and Applied Mathematics. In all human activities one collects measurements subject to variability and leading to the classical concepts of Probability and Mathematical Statistics that can modelize “observations” : random variables, samples, point process

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A Collection of Examples, for which the kernel and the associated norm and space are explicitly described. They can be used to illustrate aspects of the theory or to practically implement some of the tools presented in the book. In Section 2 and 3 we give examples of effective constructions of kernels. In Section 2 we apply

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rocesses) 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 accident

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