Bucchia, Beatrice (2014). Testing for epidemic changes in the mean of a multiparameter stochastic process. J. Stat. Plan. Infer., 150. S. 124 - 142. AMSTERDAM: ELSEVIER SCIENCE BV. ISSN 1873-1171
Full text not available from this repository.Abstract
In this paper, multiparameter stochastic processes {Z(n)(x)}(x is an element of[0, n]d), n is an element of N, are tested for the occurrence of a block (k(0), m(0)] = (k(0,1), m(0,1)] x ... x (k(0,d), m(0,d)] subset of [0, n](d) where the mean of the process changes. This is modeled in the form Z(n)(x) = lambda((0) under bar,x])mu(n) + sigma Y(x)+lambda((0) under bar, x] boolean AND (k(0), m(0)])delta(n) where (0) under bar = (0,..., 0)', lambda(A) denotes the Lebesgue measure of a set A subset of R-d, and mu(n), delta(n) is an element of R as well as 0 < sigma < infinity are unknown parameters. The stochastic process [Y-n(t) = Y ([nt]) : t is an element of[0,1](d)} is assumed to fulfill a weak invariance principle. Under the null hypothesis, an approximation for the tail behavior of the limit variable of a trimmed maximum-type test statistic is given. Then, the (weak) consistency of the test under the alternative is proven. The corresponding estimation problem for the points k(0) and m(0) is also considered and consistent estimators are given for local alternatives delta(n) = delta n(-d/2) with delta not equal 0. (C) 2014 Elsevier B.V. All rights reserved.
Item Type: | Journal Article | ||||||||
Creators: |
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URN: | urn:nbn:de:hbz:38-434963 | ||||||||
DOI: | 10.1016/j.jspi.2014.03.001 | ||||||||
Journal or Publication Title: | J. Stat. Plan. Infer. | ||||||||
Volume: | 150 | ||||||||
Page Range: | S. 124 - 142 | ||||||||
Date: | 2014 | ||||||||
Publisher: | ELSEVIER SCIENCE BV | ||||||||
Place of Publication: | AMSTERDAM | ||||||||
ISSN: | 1873-1171 | ||||||||
Language: | English | ||||||||
Faculty: | Unspecified | ||||||||
Divisions: | Unspecified | ||||||||
Subjects: | no entry | ||||||||
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URI: | http://kups.ub.uni-koeln.de/id/eprint/43496 |
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