• Journal of the Korean Statistical Society
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• v.16 no.2
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• pp.117-127
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• 1987

The Simpson's paradox is a paradoxical phenomenon which might occur when analyzing $2 \times 2$ contingency table. This paper considers the role of probability assignment of the experimental units in reducing the chances of Simpson's paradox. Numerical results are given to illustrate how the chance of Simpson's paradox behaves.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1045-1056
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• 2007

We consider M/M/1 feedback queues with multi-class customers. We assume that different classes of customers have different arrival rates, service rates and feedback probabilities. Using the h-transforms of McDonald(999) we derive an importance sampling estimator for an overflow probability that the total number of customers in the system reaches a high level before emptying.

• Journal of Korean Society for Quality Management
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• v.5 no.2
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• pp.3-20
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• 1977

The purpose of this Study is to develope the Role of Statistics in Industrial mass production. The process of mass production will be divided into three steps, that is, Standardization, production and inspection. The Statistics is applied to Specificat-ions, Quality Control and Sampling inspection in these three steps. The applications have developed to Statistical methods based on probability theory. And then, The improved plan is exhibited the point of problems of introducting of spreading of quality control throughout field survey.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.359-369
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• 2005

Central limit theorem is known as one of the most important limit theorem in statistics and probability. This paper provides a dynamic MS Excel program that demonstrates computer simulation of various types of central limit theorems. Our result will be of great use for better understanding of central limit theorems.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.41-51
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• 1994

We consider nonparametric procedures for the selection and ranking problems. Tukey's generalized lambda distribution is condidered as the distribution for the score function because the distribution can approximate many well-known contionuous distributions. Also we compare these procedures in terms of efficiency, defined by the ratio of a probability of a correct selection divided by the expected selected subset size.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.843-850
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• 2006

In this paper, we consider the Bayesian multiple comparisons problem for K bivariate exponential populations to make inferences on the relationships among the parameters based on observations. And we suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Also, we give a numerical examples to illustrate our procedure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.116-120
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• 2008

Clustering is a method for unsupervised learning. General clustering tools have been depended on statistical methods and machine learning algorithms. One of the popular clustering algorithms based on machine learning is the self organizing map(SOM). SOM is a neural networks model for clustering. SOM and extended SOM have been used in diverse classification and clustering fields such as data mining. But, SOM has had a problem determining optimal number of clusters. In this paper, we propose an improvement of SOM using gap statistic and probability distribution. The gap statistic was introduced to estimate the number of clusters in a dataset. We use gap statistic for settling the problem of SOM. Also, in our research, weights of feature nodes are updated by probability distribution. After complete updating according to prior and posterior distributions, the weights of SOM have probability distributions for optima clustering. To verify improved performance of our work, we make experiments compared with other learning algorithms using simulation data sets.

• Journal of the Korean Statistical Society
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• v.25 no.2
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• pp.205-216
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• 1996

The bootstrap calibration method for empirical likelihood is considered to make a confidence region for the regression coefficients. Asymptotic properties are studied regarding the coverage probability. Small sample simulation results reveal that the bootstrap calibration works quite well.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.177-189
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• 2003

For a positive integer m, operator m-semi-stability and the strict operator m-semi-stability of probability measures on R^d$ are defined. The operator m-semi-stability is a generalization of the definition of operator semi-stability with exponent Q. Characterization of strictly operator na-semi-stable distributions among operator m-semi-stable distributions is given. Translation of strictly operator m-semi-stable distribution is discussed.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.407-416
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• 1997

Suppose that { $X_{i}$ } is a stationary AR(1) process and { $Y_{j}$ } is an ARX process with { $X_{i}$ } as exogeneous variables. Let $Y_{j}$ $^{*}$ be the stochastic process which is the sum of $Y_{j}$ and a nonstochastic trend. In this paper we consider the problem of estimating the conditional probability that $Y_{{n+1}}$$^{*}$ is bigger than $X_{{n+1}}$, given $X_{1}$, $Y_{1}$$^{*}$,..., $X_{n}$ , $Y_{n}$ $^{*}$. As an estimator for the tolerance probability, an Mann-Whitney statistic based on least squares residuars is suggested. It is shown that the deviations between the estimator and true probability are stochatically bounded with $n^{{-1}$2}/ order. The result may be applied to the stress-strength reliability theory when the stress and strength variables violate the classical iid assumption.umption.n.