MULTIVARIATE EXPONENTIAL AND GEOMETRIC DISTRIBUTIONS WITH LIMITED MEMORY

被引:12
|
作者
MARSHALL, AW
OLKIN, I
机构
[1] STANFORD UNIV,STANFORD,CA 94305
[2] WESTERN WASHINGTON UNIV,BELLINGHAM,WA 98225
关键词
CHARACTERIZATION OF DISTRIBUTIONS; MULTIVARIATE EXPONENTIAL DISTRIBUTIONS; MULTIVARIATE GEOMETRIC DISTRIBUTIONS; FUNCTIONAL EQUATIONS;
D O I
10.1006/jmva.1995.1027
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Many connections between geometric and exponential distributions are known. Characterizations and derivations of these distributions often run parallel. Moreover, one kind of distribution can be derived from the other: exponential distributions are limits of sequences of rescaled geometric distributions, and the integral parts of exponential random variables have geometric distributions. The lack of memory property is expressed by functional equations of the form ($) over bar F(x + u) = ($) over bar F(x) ($) over bar F(u) for all (x, u) is an element of S, where ($) over bar F(x) = P{X(1) > x(1), ..., X(n) > x(n)}. With S = R(+)(2n), the equation expresses a complete lack of memory that is possessed only by distributions with independent exponential marginals. But when S is a proper subset of R(+)(2n), the functional equation expresses a partial lack of memory property that in some cases is possessed by a more interesting family of multivariate exponential distributions, as for example, those with exponential minima. In this paper appropriate choices for S and the resulting families of solutions are investigated, together with the associated families of multivariate geometric distributions. (C) 1995 Academic Press, Inc.
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页码:110 / 125
页数:16
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