• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.415-431
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• 2002

A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.647-653
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• 2015

Extreme value theory concerns the distributional properties of the maximum of a random sample; subsequently, it has been significantly extended to stationary random sequences satisfying weak dependence restrictions. We focus on distributional mixing condition $D(u_n)$ and the Berman condition based on covariance among weak dependence restrictions. The former is assumed for general stationary sequences and the latter for stationary normal processes; however, both imply the same distributional limit of the maximum of the normal process. In this paper $D(u_n)$ condition is shown weaker than Berman's covariance condition. Examples are given where the Berman condition is satisfied but the distributional mixing is not.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.749-764
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• 2003

In this paper we explain that normal theory likelihood-ratio tests(z, t, $x^2$. F) for mean(s) or variance(s) can be geometrically related to volume of difference of two joint pdf's. One is an estimated joint pdf under null parameter space $\omega$ and the other is an estimated joint pdf under full parameter space $\Omega$. For explanations, ‘distance between two distributions’ is defined. We study properties of it, and derive some results on the distance between two multivariate normal distributions.

• Journal of the Korean Chemical Society
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• v.15 no.6
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• pp.285-293
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• 1971

The statistical thermodynamical properties of heavy water are calculated according to the transient state theory of significant liquid structure. The calculated values are shown to be in good agreement with the observed ones. The grand canonical ensemble partition function for the adsorbed phase of heavy water on graphite surface is derived using the theory. The adsorption isotherm, the surface pressure, the molar entropy and the molar internal energy for the adsorbed phase and then the molar heat of adsorption are calculated according to the derived partition function. The thermodynamic properties of the adsorbed water are also calculated and the results are compared with those of heavy water and discussed in view of the experimentally observed phenomena.

• 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.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.49-60
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• 2006

There are six approaches to constructing standardized coefficient for logistic regression. The standardized coefficient based on Kruskal's information theory is known to be the best from a conceptual standpoint. In order to calculate this standardized coefficient, the coefficient of determination based on entropy loss is used among many kinds of coefficients of determination for logistic regression. In this paper, this standardized coefficient is obtained by using four kinds of coefficients of determination which have the most intuitively reasonable interpretation as a proportional reduction in error measure for logistic regression. These four kinds of the sixth standardized coefficient are compared with other kinds of standardized coefficients.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.141-146
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• 2009

Support vector machine is a classification algorithm based on statistical learning theory. It has shown many results with good performances in the data mining fields. But there are some problems in the algorithm. One of the problems is its heavy computing cost. So we have been difficult to use the support vector machine in the dynamic and online systems. To overcome this problem we propose to use stratified sampling of statistical sampling theory. The usage of stratified sampling supports to reduce the size of training data. In our paper, though the size of data is small, the performance accuracy is maintained. We verify our improved performance by experimental results using data sets from UCI machine learning repository.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.196-201
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• 2008

Statistical learning theory has three analytical tools which are support vector machine, support vector regression, and support vector clustering for classification, regression, and clustering respectively. In general, their performances are good because they are constructed by convex optimization. But, there are some problems in the methods. One of the problems is the subjective determination of the parameters for kernel function and regularization by the arts of researchers. Also, the results of the learning machines are depended on the selected parameters. In this paper, we propose an efficient method for objective determination of the parameters of support vector clustering which is the clustering method of statistical learning theory. Using evolutionary algorithm and bootstrap method, we select the parameters of kernel function and regularization constant objectively. To verify improved performances of proposed research, we compare our method with established learning algorithms using the data sets form ucr machine learning repository and synthetic data.

• English Language & Literature Teaching
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• v.17 no.2
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• pp.93-114
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• 2011

The aim of this study is twofold. First, this study aimed to explore how Korean university students' English learning motivation is related to their English listening proficiency and study time. Second, it attempted to interpret the English learning motivation linking the two different motivation theories: self-determination theory and L2 motivational self system. The constructs of the students' L2 learning motivation were investigated with the data obtained through the questionnaire from 122 sophomore students. A factor analysis was conducted to extract the major factors of motivation. As a result, 6 factors were extracted: Intrinsic Pleasure, Identified Value Regulation, Intrinsic Accomplishment, Introjected Regulation, External Regulation, and Identified Regulation. The Interrelatedness among the assessment results on the L2 listening proficiency (pre and post test), listening study time, and motivation factors was measured by correlation coefficients. The statistical results indicated that pre-test scores were significantly related to Identified Regulation and Identified Value Regulation toward English learning, and post-test results had significant correlation with Intrinsic Accomplishment and Identified Regulation. However, no motivation subtypes showed statistical association with the students' listening study time. The results were attempted to be interpreted both under L2 motivational self system and self-determination framework to better illuminate the motivation theory with more explanatory power.

• Journal of Korean Library and Information Science Society
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• v.13
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• pp.131-166
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• 1986

This study is designed to review the methods of duplicate copies decision making in the academic library. In this thesis, I surveyed queueing & markov model, statistical model, and simulation model. The contents of the study can be summarized as follows: 1) Queueing and markov model is used for one of duplicate copies decision-making methods. This model was suggested by Leimkuler, Morse, and Chen, etc. Leimkuler proposed growth model, storage model, and availability model through using system analysis method. Queueing theory is a n.0, pplied to Leimkuler's availability model. Morse ad Chen a n.0, pplied queueing and markov model to their theory. They used queueing theory for measuring satisfaction level and Markov model for predicting user demand. 2) Another model of duplicate copies decision-making methods is statistical model. This model is suggested by Grant and Sohn, Jung Pyo. Grant suggested a model with a formula to satisfy the user demand more than 95%, Sohn, Jung Pyo suggested a model with two formulars: one for duplicate copies decision-making by using standard deviation and the other for duplicate copies predicting by using coefficient of variation. 3) Simulation model is used for one of duplicate copies decision-making methods. This model is suggested by Buckland and Arms. Buckland considered both loan period and duplicate copies simultaneously in his simulation model. Arms suggested computer-simulation model as one of duplicate copies decision-making methods. These methods can help improve the efficiency of collection development and solve some problems (space, staff, budget, etc, ) of Korean academic libraries today.