• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.595-600
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• 1999

We present a simple geometric approach which uses polar transformation and elementary trigonometry to evaluating an orthant probability in a bivariate normal distribution. Figures are provided to illustrate the situation for varying correlation coefficient. We derive the distribution of the sample correlation coefficient from a bivariate normal distribution when the sample size is 2 as an application.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.139-151
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• 2004

Kim et al. (2002) developed public use SAS-based software for two-way stratification design, which is called SOCSLP We describe the details of a new approach implemented using SOCSLP and key differences between the approach and the sampling schemes of Sitter and Skinner (1994) and Winkler (2001). In addition, a numerical example is given to compare those methods with respect to the probabilities of selecting sample arrays.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.647-654
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• 2003

Bayesian probability models for finite populations are considered assuming so-called the super-population. We find the posterior distribution of population mean by a new approach, using the concept of pivotal quantity for the small sample case. A large sample theory is also treated throught the concept of asymptotically pivotal quantity.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.357-366
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• 1999

Let us assume that two different log-linear models are selected by various model selection methods. When these are non-hierarchical it is not easy to choose one of these models. In this paper the well-known Cox's statistic is applied to compare these non-hierarchical log-linear models. Since it is impossible to obtain the analytic solution about the problem we proposed a alternative method by extending Pesaran and pesaran's (1993) simulation approach. We find that the values of proposed test statistic and the estimates are very much stable with some empirical results.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.21-32
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• 2016

We study asymptotic expansion formulae for numerical computation of Greeks (i.e. sensitivity) in finance. Our approach is based on the integration-by-parts formula of the Malliavin calculus. We propose asymptotic expansion of Greeks for a stochastic volatility model using the Greeks formula of the Black-Scholes model. A singular perturbation method is applied to derive asymptotic Greeks formulae. We also provide numerical simulation of our method and compare it to the Monte Carlo finite difference approach.

• Journal of the Korean Statistical Society
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• v.22 no.1
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• pp.1-12
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• 1993

An approach to make the information bound sharper in median-unbiased estimation, based on an analogue of the Cramer-Rao inequality developed by Sung et al. (1990), is introduced for continuous densities with a nuisance parameter by considering information quantities contained both in the parametric function of interest and in the nuisance parameter in a linear fashion. This approach is comparable to that of improving the information bound in mean-unbiased estimation for the case of two unknown parameters. Computation of an optimal weight corresponding to the nuisance parameter is also considered.

• 전기의세계
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• v.22 no.2
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• pp.51-56
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• 1973

The comparative study of maximum likelihood estimation with Bayesian approach was made by statistical & computational methods in center of a priori information of static systems and the effect of a priori information on the accuracy of the estimatiion was also analyzed. Through the numerical computations of some examples by digital computer, we concluded that maximum likelihood method is better than Bayesian estimation except for almost certain a priori informations. The study may therefore contribute in identification problems of dynamical systems connected with a priori informations.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.109-115
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• 2001

Wavelet coefficients are known to have decorrelating properties, since wavelet is orthonormal transformation. but empirically, those wavelet coefficients of images, like edges, are not statistically independent. Jansen and Bultheel(1999) developed the empirical Bayes approach to improve the classical threshold algorithm using local characterization in Markov random field. They consider the clustering of significant wavelet coefficients with uniform distribution. In this paper, we developed wavelet thresholding algorithm using Laplacian distribution which is more realistic model.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.219-227
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• 2001

Another approach (multi-parameter measurement method) of interlaboratory studies of test methods is presented. When the unrestricted normal likelihood for the fixed latent variable model is unbounded, we propose a me쇙 of restricting the parameter space by formulating realistic alternative hypothesis under which the likelihood is bounded. A simulation study verified the claim of conservatism of level of significance based on assumptions about central chi-square distributed test statistics and on Bonferroni approximations. We showed a randomization approach that furnished empirical significance levels would be better than a Bonferroni adjustment.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.283-298
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• 2004

We present a trial solution approach to GI/M/l queues with generalized vacations. Specific types of generalized vacations we consider are N -policy and a combination of N-policy and exponential multiple vacations. Discussions about how to find trial solutions are given.