• Title/Summary/Keyword: extended negative quadrant dependence

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A Family of Extended NQD Bivariate Distributions with Continuous Marginals

  • Ryu, Dae-Hee
    • Communications for Statistical Applications and Methods
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    • v.19 no.1
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    • pp.85-95
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    • 2012
  • In this paper we define extended negative quadrant dependence which is weaker negative quadrant dependence and show conditions for having extended negative quadrant dependence property. We also derive generalized Farlie-Gumbel-Morgenstern uniform distributions that possess the extended quadrant dependence property.

ON THE LIMIT BEHAVIOR OF EXTENDED NEGATIVE QUADRANT DEPENDENCE

  • Baek, Jong-Il;Lee, Gil-Hwan
    • Honam Mathematical Journal
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    • v.32 no.4
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    • pp.689-699
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    • 2010
  • We discuss in this paper the notions of extended negative quadrant dependence and its properties. We study a class of bivariate uniform distributions having extended negative quadrant dependence, which is derived by generalizing the uniform representation of a well-known Farlie-Gumbel-Morgenstern distribution. Finally, we also study the limit behavior on the extended negative quadrant dependence.

On Complete Convergence for Weighted Sums of Pairwise Negatively Quadrant Dependent Sequences

  • Ko, Mi-Hwa
    • Communications for Statistical Applications and Methods
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    • v.19 no.2
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    • pp.247-256
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    • 2012
  • In this paper we prove the complete convergence for weighted sums of pairwise negatively quadrant dependent random variables. Some results on identically distributed and negatively associated setting of Liang and Su (1999) are generalized and extended to the pairwise negative quadrant dependence case.

A weakly dependence concepts of bivariate stochastic processes

  • Choi, Jeong-Yeol;Baek, Jong-Il;Youn, Eun-Ho
    • Communications of the Korean Mathematical Society
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    • v.11 no.3
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    • pp.831-839
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    • 1996
  • In the last years there has been growing interest in concepts of positive (negative) dependence of stochastic processes such that concepts are considerable us in deriving inequalities in probability and statistics. Lehmann [7] introduced various concepts of positive(negative) dependence in the bivariate case. Stronger notions of bivariate positive(negative) dependence were later developed by Esary and Proschan [6]. Ahmed et al.[2], and Ebrahimi and Ghosh[5] obtained multivariate versions of various positive(negative) dependence as described by Lehmann[7] and Esary and Proschan[6]. Concepts of positive(negative) dependence for random variables have subsequently been extended to stochastic processes in different directions by many authors.

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On the Conditionally Independent and Positive and Negative Dependence of Bivariate Stochastic Processes

  • Baek, Jong Il;Han, Kwang Hee
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.367-379
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    • 2002
  • We introduce a new concept of $\theta$ conditionally independent and positive and negative dependence of bivariate stochastic processes and their corresponding hitting times. We have further extended this theory to stronger conditions of dependence similar to those in the literature of positive and negative dependence and developed theorems which relate these conditions. Finally we are given some examples to illustrate these concepts.