• Title/Summary/Keyword: Maximum Independence

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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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NOTE ON UPPER BOUND SIGNED 2-INDEPENDENCE IN DIGRAPHS

  • Kim, Hye Kyung
    • East Asian mathematical journal
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    • v.28 no.5
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    • pp.579-585
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    • 2012
  • Let D be a finite digraph with the vertex set V(D) and arc set A(D). A two-valued function $f:V(D){\rightarrow}\{-1,\;1\}$ defined on the vertices of a digraph D is called a signed 2-independence function if $f(N^-[v]){\leq}1$ for every $v$ in D. The weight of a signed 2-independence function is $f(V(D))=\sum\limits_{v{\in}V(D)}\;f(v)$. The maximum weight of a signed 2-independence function of D is the signed 2-independence number ${\alpha}_s{^2}(D)$ of D. Recently, Volkmann [3] began to investigate this parameter in digraphs and presented some upper bounds on ${\alpha}_{s}^{2}(D)$ for general digraph D. In this paper, we improve upper bounds on ${\alpha}_s{^2}(D)$ given by Volkmann [3].

Test for Independence in Bivariate Weibull Model under Bivariate Random Censorship

  • Cho, Jang-Sik;Cho, Kil-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.789-797
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    • 2003
  • In this paper, we consider two components system which have bivariate weibull model with bivariate random censored data. We proposed large sample test for independence based on maximum likelihood estimator and relative frequency estimator, respectively. Also we derive asymptotic properties for the large sample tests and present a numerical study.

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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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Estimation of Design Rainfall Using 3 Parameter Probability Distributions (3변수 확률분포에 의한 설계강우량 추정)

  • Lee, Soon Hyuk;Maeng, Sung Jin;Ryoo, Kyong Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.595-598
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    • 2004
  • This research seeks to derive the design rainfalls through the L-moment with the test of homogeneity, independence and outlier of data on annual maximum daily rainfall at 38 rainfall stations in Korea. To select the appropriate distribution of annual maximum daily rainfall data by the rainfall stations, Generalized Extreme Value (GEV), Generalized Logistic (GLO), Generalized Pareto (GPA), Generalized Normal (GNO) and Pearson Type 3 (PT3) probability distributions were applied and their aptness were judged using an L-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test. Parameters of appropriate distributions were estimated from the observed and simulated annual maximum daily rainfall using Monte Carlo techniques. Design rainfalls were finally derived by GEV distribution, which was proved to be more appropriate than the other distributions.

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Frequency Analysis of Extreme Rainfall Using 3 Parameter Probability Distributions (3변수 확률분포형에 의한 극치강우의 빈도분석)

  • Kim, Byeong-Jun;Maeng, Sung-Jin;Ryoo, Kyong-Sik;Lee, Soon-Hyuk
    • Journal of The Korean Society of Agricultural Engineers
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    • v.46 no.3
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    • pp.31-42
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    • 2004
  • This research seeks to derive the design rainfalls through the L-moment with the test of homogeneity, independence and outlier of data on annual maximum daily rainfall at 38 rainfall stations in Korea. To select the appropriate distribution of annual maximum daily rainfall data by the rainfall stations, Generalized Extreme Value (GEV), Generalized Logistic (GLO), Generalized Pareto (GPA), Generalized Normal (GNO) and Pearson Type 3 (PT3) probability distributions were applied and their aptness were judged using an L-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test. Parameters of appropriate distributions were estimated from the observed and simulated annual maximum daily rainfall using Monte Carlo techniques. Design rainfalls were finally derived by GEV distribution, which was proved to be more appropriate than the other distributions.

Monetary Policy Independence and Bond Yield in Developing Countries

  • ANWAR, Cep Jandi;SUHENDRA, Indra
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.11
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    • pp.23-31
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    • 2020
  • This paper investigates the impact of monetary policy independence shock on bond yield by allowing for heterogeneous coefficients in the model based on panel data for 19 developing countries using quarterly data from 1991 to 2016. First, we estimate the model using conventional panel VAR estimation with the assumption of homogeneous coefficients across countries. Second, by performing Chow and Roy-Zellner tests to check the homogeneity assumption, we find that the assumption does not hold in the model. Third, we apply a mean-group estimation for panel VAR as a solution for heterogeneity panel model. The results reveal that central bank independence is effective in reducing bond yield with the maximum at period 6 after the shock. Shock one standard deviation bond yield has a negative effect on consumption and investment. We determine that central bank independence has a contradictory effect on real activity; a negative effect on consumption but a positive influence on investment for the first two years after the shock. Additionally, we split our sample into three groups to make the subgroups pool. Our empirical result shows that monetary policy independence shock reduces bond yield. Meanwhile, the response of economic activity to bond yield varies for all three groups.

Large Sample Tests for Independence and Symmetry in the Bivariate Weibull Model under Random Censorship

  • Cho, Jang-Sik;Ko, Jeong-Hwan;Kang, Sang-Kil
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.405-412
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    • 2003
  • In this paper, we consider two components system which the lifetimes have a bivariate weibull distribution with random censored data. Here the censoring time is independent of the lifetimes of the components. We construct large sample tests for independence and symmetry between two-components based on maximum likelihood estimators and the natural estimators. Also we present a numerical study.

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UNIFYING STATIONARY EQUATIONS FOR GENERALIZED CANONICAL CORRELATION ANALYSIS

  • Kang Hyun-Cheol;Kim Kee-Young
    • Journal of the Korean Statistical Society
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    • v.35 no.2
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    • pp.143-156
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    • 2006
  • In the present paper, various solutions for generalized canonical correlation analysis (GCCA) are considered depending on the criteria and constraints. For the comparisons of some characteristics of the solutions, we provide with certain unifying stationary equations which might to also useful to obtain various generalized canonical correlation analysis solutions. In addition, we suggest an approach for the generalized canonical correlation analysis by exploiting the concept of maximum eccentricity originally de-signed to test the internal independence structure. The solutions, including new one, are compared through unifying stationary equations and by using some numerical illustrations. A type of iterative procedure for the GCCA solutions is suggested and some numerical examples are provided to illustrate several GCCA methods.