• Title/Summary/Keyword: Statistical Procedures

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The Moore-Penrose Inverse for the Classificatory Models

  • Kim, Byung-Chun;Lee, Jang-Taek
    • Journal of the Korean Statistical Society
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    • v.15 no.1
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    • pp.46-61
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    • 1986
  • Many procedures for deriving the Moore-Penrose invese $X^+$ have been developed, but the explicit forms of Moore-Penerose inverses for design matrices in analysis of variance models are not known heretofore. The purpose of this paper is to find explicit forms of $X^+$ for the one-way and the two-way analysis of variance models. Consequently, the Moore-Penerose inverse $X^+$ and the shortest solutions of them can be easily obtained to the level of pocket calculator by way of our results.

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Empirical Bayes Estimation of the Binomial and Normal Parameters

  • Hong, Jee-Chang;Inha Jung
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.87-96
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    • 2001
  • We consider the empirical Bayes estimation problems with the binomial and normal components when the prior distributions are unknown but are assumed to be in certain families. There may be the families of all distributions on the parameter space or subfamilies such as the parametric families of conjugate priors. We treat both cases and establish the asymptotic optimality for the corresponding decision procedures.

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Maximum Likelihood Estimation for the Laplacian Autoregressive Time Series Model

  • Son, Young-Sook;Cho, Sin-Sup
    • Journal of the Korean Statistical Society
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    • v.25 no.3
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    • pp.359-368
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    • 1996
  • The maximum likelihood estimation is discussed for the NLAR model with Laplacian marginals. Since the explicit form of the estimates cannot be obtained due to the complicated nature of the likelihood function we utilize the automatic computer optimization subroutine using a direct search complex algorithm. The conditional least square estimates are used as initial estimates in maximum likelihood procedures. The results of a simulation study for the maximum likelihood estimates of the NLAR(1) and the NLAR(2) models are presented.

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NONPARAMETRIC ONE-SIDED TESTS FOR MULTIVARIATE AND RIGHT CENSORED DATA

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.32 no.4
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    • pp.373-384
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    • 2003
  • In this paper, we formulate multivariate one-sided alternatives and propose a class of nonparametric tests for possibly right censored data. We obtain the asymptotic tail probability (or p-value) by showing that our proposed test statistics have asymptotically multivariate normal distributions. Also, we illustrate our procedure with an example and compare it with other procedures in terms of empirical powers for the bivariate case. Finally, we discuss some properties of our test.

Comparing More than Two Agreement Measures Using Marginal Association

  • Oh, Myong-Sik
    • Communications for Statistical Applications and Methods
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    • v.16 no.6
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    • pp.1023-1029
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    • 2009
  • Oh (2009) has proposed a likelihood ratio test for comparing two agreements for dependent observations based on the concept of marginal homogeneity and marginal stochastic ordering. In this paper we consider the comparison of more than two agreement measures. Simple ordering and simple tree ordering among agreement measures are investigated. Some test procedures, including likelihood ratio test, are discussed.

ON THE RATIO X/(X + Y) FOR WEIBULL AND LEVY DISTRIBUTIONS

  • ALI M. MASOOM;NADARAJAH SARALEES;WOO JUNGSOO
    • Journal of the Korean Statistical Society
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    • v.34 no.1
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    • pp.11-20
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    • 2005
  • The distributional properties of R = X/(X + Y) and related estimation procedures are derived when X and Y are independent and identically distributed according to the Weibull or Levy distribution. The work is of interest in biological and physical sciences, econometrics, engineering and ranking and selection.

Bayesian Prediction under Dynamic Generalized Linear Models in Finite Population Sampling

  • Dal Ho Kim;Sang Gil Kang
    • Communications for Statistical Applications and Methods
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    • v.4 no.3
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    • pp.795-805
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    • 1997
  • In this paper, we consider a Bayesian forecasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under dynamic generalized linear models. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

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BQUE, AOV and MINQUE procedure in Estimating Variance Components

  • Huh, Moon-Yul
    • Journal of the Korean Statistical Society
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    • v.9 no.1
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    • pp.97-108
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    • 1980
  • Variance components model appears often in designing experiments including time series data analysis. This paper is investigating the properties of the various procedures in estimating variance components for the two-way random model without interaction under normality. In this age of computer-oriented computations, MINQUE is found to be quite practicla because of the robustness with respect to the design configurations and parameters. Also adjusted AOV type estimation procedure is found to yield superior results over the unadjusted one.

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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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