• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.309-316
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• 2007

In this paper, we decompose the whole likelihood based on grouped data into conditional likelihoods and study the approximate contribution of additional inspection to the efficiency. We also combine the conditional maximum likelihood estimators to construct an approximate maximum likelihood estimator. For an exponential distribution, we see that a large inspection size does not increase the efficiency much if the failure rate is small, and the maximum likelihood estimator can be approximated with a linear function of inspection times.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.367-386
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• 2002

The Present paper is devoted to a study of the performance, in large samples, of a conditional maximum likelihood estimator(CMLE) for the parameter ${\lambda}$ in a pure birth processes(PBP). To conduct the conditional inference for the PBP, we drove the likelihood function of time-inhomogeneous Poisson processes. The limiting distributions of CMLE under the likelihoods $L_{t}$ or $\overline{L_{t}}$ are investigated. We found that the CMLE is asymptotically efficient with respect to the both $L_{t}$ or $\overline{L_{t}}$ under the efficiency criterion of Weiss & Wolfowitz(1974).

• 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.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.453-465
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• 1997

The family of power-divergence statistics conditional on margins is considered for testing homogeneity of .tau. multinomial populations with equal sample size and the exact Bahadur slope is obtained. It is shown that the likelihood ratio test conditional on margins is the most Bahadur efficient among the family of power-divergence statistics.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1133-1138
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• 2008

A general method of detecting outliers based on a change of likelihood by using the influence function is suggested. It can be applied to all kinds of distributions that are specified by parameters. For the multivariate normal case, specific computations are made to get the corresponding conditional influence function. A numerical example is provided for illustration.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.193-200
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• 2000

Modelling the dependence via random effects in censored multivariate survival data has recently received considerable attention in the biomedical literature. The random effects models model not only the conditional survival times but also the conditional hazard rate. Systematic likelihood inference for the models with random effects is possible using Lee and Nelder's (1996) hierarchical-likelihood (h-likelihood). The purpose of this presentation is to introduce Ha et al.'s (2000a,b) inferential methods for the random effects models via the h-likelihood, which provide a conceptually simple, numerically efficient and reliable inferential procedures.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.76-81
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• 2010

In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the second-order conditional maximum a posteriori (CMAP). In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the current observation and the speech activity decisions in the pervious two frames. Experimental results show that the proposed approach yields better results compared to the statistical model-based and the CMAP-based VAD using the LR test.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.489-497
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• 1996

Lower bounds for the full level probabilities are derived under order restrictions in weights. Discussions are made on typical isotonic cones such as linear order, simple tree order, and unimodal order cones. We also discuss applications of these results for constructing conditional likelihood ratio tests for ordered hypotheses in a contingency table. A real data set on torus mandibularis will be analyzed for illustrating the testing procedure.

• Journal of the Korean Statistical Society
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• v.9 no.1
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• pp.13-29
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• 1980

The statistical theory of factor analysis is briefly reviewed with emphasis on the maximum-likelihood method. A modified version of Joreskog(1975) is used for the implementation of the maximum-likelihood method. For the minimization of the conditional minimum function, an adaptive Newton-Raphson method is applied.

• 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.