• Title/Summary/Keyword: statistical 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.

Tests For and Against a Positive Dependence Restriction in Two-Way Ordered Contingency Tables

  • Oh, Myongsik
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.205-220
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    • 1998
  • Dependence concepts for ordered two-way contingency tables have been of considerable interest. We consider a dependence concept which is less restrictive than likelihood ratio dependence and more restrictive than regression dependence. Maximum likelihood estimation of cell probability under this dependence restriction is studied. The likelihood ratio statistics for and against this dependence are proposed and their large sample distributions are derived. A real data is analyzed to illustrate the estimation and testing procedures.

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A Weak Positive Orthant Dependence Concept

  • Hye-Young Seo;Tae-Sung Kim
    • Communications for Statistical Applications and Methods
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    • v.5 no.1
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    • pp.193-203
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    • 1998
  • In this paper, we introduce a new concept of the multivariate positive dependence. This concept is weaker than the positive orthant dependence. Some basic properties and preservation results are presented.

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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.

Estimation of Spatial Dependence by Quasi-likelihood Method (의사우도법을 이용한 공간 종속 모형의 추정)

  • 이윤동;최혜미
    • The Korean Journal of Applied Statistics
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    • v.17 no.3
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    • pp.519-533
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    • 2004
  • In this paper, we suggest quasi-likelihood estimation (QLE) method and its robust version in estimating spatial dependence modelled through variogram used for spatial data modelling. We compare the statistical characteristics of the estimators with other popular least squares estimators of parameters for variogram model by simulation study. The QLE method for estimating spatial dependence has the advantages that it does not need the concept of lags commonly required for least squares estimation methods as well as its statistical superiority. The QLE method also shows the statistical superiority to the other methods for the tested Gaussian and non-Gaussian spatial processes.

On Information Theoretic Index for Measuring the Stochastic Dependence Among Sets of Variates

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.26 no.1
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    • pp.131-146
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    • 1997
  • In this paper the problem of measuring the stochastic dependence among sets fo random variates is considered, and attention is specifically directed to forming a single well-defined measure of the dependence among sets of normal variates. A new information theoretic measure of the dependence called dependence index (DI) is introduced and its several properties are studied. The development of DI is based on the generalization and normalization of the mutual information introduced by Kullback(1968). For data analysis, minimum cross entropy estimator of DI is suggested, and its asymptotic distribution is obtained for testing the existence of the dependence. Monte Carlo simulations demonstrate the performance of the estimator, and show that is is useful not only for evaluation of the dependence, but also for independent model testing.

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Estimation of Spatial Dependence with GEE

  • Lee, Yoon-Dong;Choi, Hye-Mi
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.269-273
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    • 2003
  • We consider an efficient parametric estimation method of spatial dependence in weak stationary processes. Spatial dependence is modeled through variogram and correlogram. Most of parametric estimation methods of correlogram use two step method; nonparametric estimation and parametric integration. We bind these two steps into one step by using GEE method instead of least squares type optimization. Our one step method is more efficient statistically and gives a clear interpretation of related concepts used in traditional two step methods.

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Stochastic Comparisons of Order Statistics under Non-standard Conditions

  • Kim, S. H.
    • Communications for Statistical Applications and Methods
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    • v.3 no.2
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    • pp.187-195
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    • 1996
  • This paper deals with the stochastic comparisons of order statistics from independent but nonidentically distributed (i.n.i.d) variates. And we consider order statistics under positive dependence, negative dependence, and exchangeability.

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Validity of Blockwise Bootstrapped Empirical Process with Multivariate Stationary Sequences

  • Kim, Tae-Yoon;Shin, Ki-Dong;Song, Gyu-Moon
    • Journal of the Korean Statistical Society
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    • v.30 no.3
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    • pp.407-418
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    • 2001
  • Buhlmann(1944) established the validity of the block bootstrap proposed by Kunsch when it is applied to p-dimensional $\alpha$-mixing dependent sequence. But his result requires a rather restrictive condition on p in the sense that p is entangled with dependence structure. We address that such restriction on p(or complication of dependence structure with p) could be removed completely when the underlying dependence structure is replace by more weakly dependent structure such as ø-mixing.

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Relationships Among Some Concepts of Multivariate Negative Dependence

  • Kim, Tae-Sung;Baek, Jong-il
    • Journal of the Korean Statistical Society
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    • v.20 no.1
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    • pp.77-83
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    • 1991
  • In this article various notions of multivariate negative dependence for random variables are obtained. Various properties and interrelationships are also derived from these notions. Several counterexamples are given to illustrate that other implications may not hold.

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