• Title/Summary/Keyword: testing independence

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Bayesian Testing for Independence in Bivariate Exponential Model

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.521-527
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    • 2006
  • In this paper, we consider the Bayesian hypotheses testing for independence in bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the fractional Bayes factor. Also we give some numerical results to illustrate our results.

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Bayesian Approach for Independence Test in Bivariate Exponential Model

  • Cho, Jang-Sik
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.327-333
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    • 2006
  • In this paper, we consider the Bayesian hypotheses testing for independence in bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the fractional Bayes factor. Also we give some numerical results to illustrate our results.

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Large Sample Test for Independence in the Bivariate Pareto Model with Censored Data

  • Cho, Jang-Sik;Lee, Jea-Man;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.377-383
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    • 2003
  • In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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Large Sample Tests for Independence in Bivariate Pareto Model with Censored Data

  • Cho, Jang-Sik;Lee, Jea-Man;Lee, Woo-Dong
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.05a
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    • pp.121-126
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    • 2003
  • In this paper, we consider two-components system which the lifetimes follow bivariate pareto model with censored data. We develop large sample tests for testing independence between two-components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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Test for Independence in Bivariate Pareto Model with Bivariate Random Censored Data

  • Cho, Jang-Sik;Kwon, Yong-Man;Choi, Seung-Bae
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.31-39
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    • 2004
  • In this paper, we consider two components system which the lifetimes follow bivariate pareto model with bivariate random censored data. We assume that the censoring times are independent of the lifetimes of the two components. We develop large sample test for testing independence between two components. Also we present a simulation study which is the test based on asymptotic normal distribution in testing independence.

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Bayes Factors for Independence and Symmetry in Freund's Bivariate Exponetial Model with Censored Data

  • Jang Sik;Dal Ho;Sang Gil
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.151-164
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    • 2000
  • In this paper we consider the Bayesian hypothese testing for independence and symmetry in Freund's bivariate exponential model with censored data In Bayesian testing problem we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. Also we derive the arithmetic and median intrinsic Bayes factors and use these results of analyze some data sets.

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Testing Independence in Contingency Tables with Clustered Data (집락자료의 분할표에서 독립성검정)

  • 정광모;이현영
    • The Korean Journal of Applied Statistics
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    • v.17 no.2
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    • pp.337-346
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    • 2004
  • The Pearson chi-square goodness-of-fit test and the likelihood ratio tests are usually used for testing independence in two-way contingency tables under random sampling. But both of these tests may provide false results for the contingency table with clustered observations. In this case we consider the generalized linear mixed model which includes random effects of clustering in addition to the fixed effects of covariates. Both the heterogeneity between clusters and the dependency within a cluster can be explained via generalized linear mixed model. In this paper we introduce several types of generalized linear mixed model for testing independence in contingency tables with clustered observations. We also discuss the fitting of these models through a real dataset.

Boostrap testing for independence in Marshall and Olkin's model under random censorship (임의중단된 이변량 지수모형의 독립성에 대한 붓스트랩 검정)

  • 김달호;조길호;조장식
    • The Korean Journal of Applied Statistics
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    • v.9 no.2
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    • pp.13-23
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    • 1996
  • In this paper, we consider the Marshall and Olkin's bivariate exponential model under random censorship for the distribution of failure times of a system with two components. We propose a bootstrap testing procedure for independence and compare the powers of it with other tests via Monte Carlo simulation.

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Bayesian Tests for Independence and Symmetry in Freund's Bivariate Exponential Model

  • Cho, Jang-Sik;Kim, Dal-Ho;Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.135-146
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    • 1999
  • In this paper, we consider the Bayesian hypotheses testing for independence and symmetry in Freund's bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the intrinsic Bayes factor. Also we derive the arithmetic and median intrinsic Bayes factors and use these results to analyze some data sets.

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Fuzzy Testing of Independence in Bivariate Normal Distribution (2변량 정규분포의 독립성에 관한 퍼지 검정)

  • Kang, Man-Ki;Seo, Hyun-A
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.1-5
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    • 2011
  • We furnished some properties of fuzzy testing of independence for correlation in a bivariate normal distribution by agreement index. First we present some restriction of the fuzzy data, define fuzzy sample correlation coefficient and agreement index for testing hypothesis with acceptance or rejection degree. Also, we show that UMP unbiased fuzzy test and drawing conclusions the fuzzy test.