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Tail behaviour of Gaussian processes with applications to the Brownian pillow

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Author Info
A.J. Koning ()
V. Protasov () (FEW-Econometrie en besliskunde)
Abstract

In this paper we investigate the tail behaviour of a random variable which may be viewed as a functional of a zero mean Gaussian process, taking special interest in the situation where the Gaussian process obeys the structure which is typical for limiting processes ocurring in nonparametric testing of [multivariate] indepencency and [multivariate] constancy over time. The tail behaviour of the random variable is described by means of a constant and a reference random variable which is defined on the same probability space as the random variable of interest. The constant acts as an upper bound, and is relevant for the computation of the efficiency of test statistics converging in distribution to the random variable of interest. The reference random variable acts as a lower bound, and is instrumental in deriving approximations for the upper percentage points of the random variable of interest by simulation.

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Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number 249.

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Date of creation: 2001
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Handle: RePEc:dgr:eureir:2001249

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Related research
Keywords: tail behaviour Gaussian processes Brownian pillow asymptotic distribution theory Kolmogorov type tests;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Kallenberg, Wilbert C. M. & Koning, Alex J., 1995. "On Wieand's theorem," Statistics & Probability Letters, Elsevier, vol. 25(2), pages 121-132, November. [Downloadable!] (restricted)
  2. Hjort, N.L. & Koning, A.J., 2001. "Constancy of distributions: nonparametric monitoring of probability distributions over time," Econometric Institute Report EI 2001-50 Revision_Date:, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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  1. N.L. Hjort & A.J. Koning, 2001. "Constancy of distributions," Econometric Institute Report 250, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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