• Title/Summary/Keyword: likelihood ratio statistics

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The likelihood ratio test for detecting the best treatment among several exponential populations (지수분표에 있어서 최우수 처리의 판별을 위한 우도비 검정)

  • 황형태
    • The Korean Journal of Applied Statistics
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    • v.8 no.1
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    • pp.151-157
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    • 1995
  • The method for detecting the best treatment is considered by means of hypothesis testing in the exponential case. The likelihood ratio test for a given hypothesis is derived to control the error probability, and the minimum powers in the interested regions are calculated to design the sampling plan.

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A Sharp Cramer-Rao type Lower-Bound for Median-Unbiased Estimators

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.23 no.1
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    • pp.187-198
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    • 1994
  • We derive a new Cramer-Rao type lower bound for the reciprocal of the density height of the median-unbiased estimators which improves most of the previous lower bounds and is attainable under much weaker conditions. We also identify useful necessary and sufficient condition for the attainability of the lower bound which is considerably weaker than those for the mean-unbiased estimators. It is shown that these lower bounds are attained not only for the family of continuous distributions with monotone likelihood ratio (MLR) property but also for the location and scale families with strong unimodal property.

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On a Bayesian P-value with the Coherence Property

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.731-740
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    • 2003
  • Schervish(1996) and Lavine and Schervish(1999) have shown that the classical P-values and the Bayes factors fail to achieve the so-called coherence property, respectively. In this paper, we propose a new type of Bayesian P-value, namely the type LR Bayesian P-value, satisfying the coherence property. The proposed Bayesian P-values are very easy to use with since they are simple functions of likelihood ratio. Their performances are discussed and compared with those of other methods under several situations.

On Testing Equality of Matrix Intraclass Covariance Matrices of $K$Multivariate Normal Populations

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.55-64
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    • 2000
  • We propose a criterion for testing homogeneity of matrix intraclass covariance matrices of K multivariate normal populations, It is based on a variable transformation intended to propose and develop a likelihood ratio criterion that makes use of properties of eigen structures of the matrix intraclass covariance matrices. The criterion then leads to a simple test that uses an asymptotic distribution obtained from Box's (1949) theorem for the general asymptotic expansion of random variables.

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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.

Testing Homogeneity of Diagonal Covariance Matrices of K Multivariate Normal Populations

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.929-938
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    • 1999
  • We propose a criterion for testing homogeneity of diagonal covariance matrices of K multivariate normal populations. It is based on a factorization of usual likelihood ratio intended to propose and develop a criterion that makes use of properties of structures of the diagonal convariance matrices. The criterion then leads to a simple test as well as to an accurate asymptotic distribution of the test statistic via general result by Box (1949).

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ORDER RESTRICTED STATISTICAL INFERENCE ON LORENZ CURVES OF PARETO DISTRIBUTIONS

  • Oh, Myongsik
    • Journal of applied mathematics & informatics
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    • v.13 no.1_2
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    • pp.457-470
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    • 2003
  • The comparison of two or more Lorenz curves of Pareto distributions of first kind under arbitrary order restriction is studied. The problem is turned out to be a statistical inference problem concerning scale parameters under order restriction. We assume that the location parameters of Palate distributions are completely unknown. In this paper the maximum likelihood estimation and likelihood ratio tests for and against order restriction are proposed.

Likelihood Ratio Test for the Epidemic Alternatives on the Zero-Inflated Poisson Model (변화시점이 있는 영과잉-포아송모형에서 돌출대립가설에 대한 우도비검정)

  • Kim, Kyung-Moo
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.247-253
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    • 1998
  • In ease of the epidemic Zero-Inflated Poisson model, likelihood ratio test was used for testing epidemic alternatives. Epidemic changepoints were estimated by the method of least squares. It were used for starting points to estimate the maximum likelihood estimators. And several parameters were compared through the Monte Carlo simulations. As a result, maximum likelihood estimators for the epidemic chaagepoints and several parameters are better than the least squares and moment estimators.

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Distribution of Votaw's $\lambda_1$(mvc) Criterion

  • Nagar, D.K.;Gupta, A.K.
    • Journal of the Korean Statistical Society
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    • v.23 no.2
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    • pp.303-323
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    • 1994
  • In this paper, distribution of Votaw's $\lambda_1$(mvc) criterion has been obtained using inverse Mellin transform, residue theorem and properties of special functions.

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Testing Outliers in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Statistical Society
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    • v.24 no.2
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    • pp.419-437
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    • 1995
  • Given the specific mean shift outlier model, several standard approaches to obtaining test statistic for outliers are discussed. Each of these is developed in detail for the nonlinear regression model, and each leads to an equivalent distribution. The geometric interpretations of the statistics and accuracy of linear approximation are also presented.

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