Positive definite distributions and subspaces of with applications to stable processes
arXiv:math/9610208
Abstract
We define embedding of an -dimensional normed space into by extending analytically with respect to the corresponding property of the classical -spaces. The well-known connection between embeddings into and positive definite functions is extended to the case of negative by showing that a normed space embeds in if and only if is a positive definite distribution. Using this criterion, we generalize the recent solutions to the 1938 Schoenberg's problems by proving that the spaces embed in if and only if We show that the technique of embedding in can be applied to stable processes in some situations where standard methods do not work. As an example, we prove inequalities of correlation type for the expectations of norms of stable vectors. In particular, for every where and are jointly -stable symmetric random variables, so that, for some the vectors and have the same distributions as and respectively, but and are independent for every choice of
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Cited by in corpus (10)
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