Multivariate cauchy distributions as locally gaussian distributions
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In the present paper, we propose a definition of locally Gaussian probability distributions of random vectors based on the linearization of their conditional quantiles. We prove that the Cauchy distribution inRn is locally Gaussian and give explicit formulas for the vectors of expectations and covariance matrices of locally Gaussian approximations. We show that locally Gaussian approximations with different dimensionalities are in some sense compatible: all of them have equal corresponding correlation coefficients. For the Cauchy distribution in a Hilbert space we prove a limit theorem on the convergence of squared finite-dimensional conditional quantiles to the stable Lévy distribution.
KeywordsCovariance Gaussian Distribution Probability Distribution Hilbert Space Limit Theorem
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- 1.H. Cramér,Mathematical Methods of Statistics, Princeton Univ. Press, Princeton (1974).Google Scholar
- 2.I. V. Proskuryakov,A Collection of Problems in Linear Algebra [in Russian], Nauka, Moscow (1970).Google Scholar
- 3.C. R. Rao,Linear Statistical Inference and Its Applications, Wiley, New York (1965).Google Scholar
- 4.L. N. Bol'shev and N. V. Smirnov,Tables of Mathematical Statistics [in Russian], Nauka, Moscow (1983).Google Scholar
- 5.V. M. Zolotarev,One-Dimensional Stable Distributions, American Mathematical Society, Providence (1986).Google Scholar