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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Applied Statistics
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Journal DOI :
The Korean Statistical Society
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Volume & Issues
Volume 17, Issue 3 - Nov 2004
Volume 17, Issue 2 - Jul 2004
Volume 17, Issue 1 - Mar 2004
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Statistical Methods for Repeated Measures Data with Three Repeat Factors
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 1~12
DOI : 10.5351/KJAS.2004.17.1.001
In this paper, we consider choosing the appropriate covariance structure for analyzing repeated measures data with three repeat factors from a study of blood pressure data, which is collected from the local residents of Yangpyeong, Gyeonggi-do (2001) and fitted linear mixed models to find the significant covariates on outcome variable(Blood Pressure)
A Study on the Measurement of Industry Agglomeration for the Census on Basic Characteristics of Establishments
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 13~26
DOI : 10.5351/KJAS.2004.17.1.013
According to economic growth theory, location configuration of business enterprises engaged in specific industries has spatial affinity. In this research we defined industrial concentration index to measure industry agglomeration using the characteristics of dispersion parameter of negative binomial distribution, and used the industrial concentration index to examine aspect of spatial configuration change. We utilized Census on Basic Characteristics of Establishments of 1995 and 2000 to deduce industrral concentration indices of 7 knowledge-based industries and 9 strategy-based industries of Choongbuk Province and analyzed the aspect of spatial configuration change.
A Modified Horvitz-Thompson Estimator by Transformation of Variables
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 27~34
DOI : 10.5351/KJAS.2004.17.1.027
The Horvitz-Thompson(H-T) estimator is less efficient than PPS estimators in some cases. We use the two-stage variable transformation in order to remove the drawbacks and increase the efficiency of H-T estimator. We transform the auxiliary variable to use the Midzuno-Sen sampling scheme at the first stage. And the next stage, we also transform the study variable to reduce the variance of H-T estimator using the inclusion probability obtained from the first transformation. We compare the efficiency between a suggested modified H-T estimator and PPS estimators.
An Approximate Shapiro -Wilk Statistic for Testing Multivariate Normality
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 35~47
DOI : 10.5351/KJAS.2004.17.1.035
In this paper, we generalizes Kim and Bickel(2003)'s statistic for bivariate normality to that of multinormality, applying Fattorini(1986)'s method. Fattorini(1986) generalized Shapiro-Wilk's statistic for univariate normality to multivariate cases. The proposed statistic could be considered as an approximate statistic to Fattorini(1986)'s. It can be used even for a big sample size. Power performance of the proposed test is assessed in a Monte Carlo study.
Noninformative Priors for the Ratio of Parameters in Inverse Gaussian Distribution
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 49~60
DOI : 10.5351/KJAS.2004.17.1.049
In this paper, when the observations are distributed as inverse gaussian, we developed the noninformative priors for ratio of the parameters of inverse gaussian distribution. We developed the first order matching prior and proved that the second order matching prior does not exist. It turns out that one-at-a-time reference prior satisfies a first order matching criterion. Some simulation study is performed.
Generalized Composite Estimators and Mean Squared Errors for l/G Rotation Design
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 61~73
DOI : 10.5351/KJAS.2004.17.1.061
Rotation sampling designs may be classified into two categories. The first type uses the same sample unit for the entire life of the survey. The second type uses the sample unit only for a fixed number of times. In both type of designs, the entire sample is partitioned into a finite number(=G) of rotation groups. This paper is generalization of the first type designs. Since the generalized design can be identified by only G rotation groups and recall level 1, we denote this rotation system as l/G rotation design. Under l/G rotation design, variance and mean squared error (MSE) of generalized composite estimator are derived, incorporating two type of biases and exponentially decaying correlation pattern. Compromising MSE's of some selected l/G designs, we investigate design efficiency, design gap effect, ans the effects of correlation and bias.
Improving the Generalization Error Bound using Total margin in Support Vector Machines
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 75~88
DOI : 10.5351/KJAS.2004.17.1.075
The Support Vector Machine(SVM) algorithm has paid attention on maximizing the shortest distance between sample points and discrimination hyperplane. This paper suggests the total margin algorithm which considers the distance between all data points and the separating hyperplane. The method extends existing support vector machine algorithm. In addition, this newly proposed method improves the generalization error bound. Numerical experiments show that the total margin algorithm provides good performance, comparing with the previous methods.
Chi-Squared Test of Independence in Case that Two Marginal Distributions are Given Exactly
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 89~103
DOI : 10.5351/KJAS.2004.17.1.089
If the given information is exact, though it is the little, we had better use it than not use in analysis. In this article, the problem of independence test in a contingency table is considered when two marginal distributions of a population are given exactly. For that case, a likelihood-ratio chi-squared test statistic and its Pearsonian type chi-squared test statistic are derived. By Monte Carlo Simulations the traditional chi-square tests and the derived tests are compared. And the related some testing problems are synthetically explained on a geometrical viewpoint.
Estimation of Population Mean Using Modified Systematic Sampling and Least Squares Method
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 105~117
DOI : 10.5351/KJAS.2004.17.1.105
In this paper, a new method is developed for estimating the mean of a population which has a linear trend. This method involves drawing a sample by the modified systematic sampling, and then estimating the population mean with an adjusted estimator, not with the sample mean itself. We use the method of least squares in determining the adjusted estimator. The proposed method is shown to be more and more efficient as the linear trend becomes stronger. It turns out to be relatively efficient as compared with the conventional methods if
the variance of the random error term in the infinite superpopulation model, is not very large.
An Estimating Method for Priority Vector in AHP, Using the Eigen-Decomposition of a Skew-Symmetric Matrix
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 119~134
DOI : 10.5351/KJAS.2004.17.1.119
Generally to estimate the priority vector in AHP, an eigen-vector method or a log-arithmic least square method is applied to pairwise comparison matrix itself. In this paper an estimating method is suggested, which is applied to pairwise comparison matrix adjusted by using the eigen-decomposition of skew-symmetric matrix. We also show theoretical background, meanings, and several advantages of this method by example. This method may be useful in case that pairwise comparison matrix is quite inconsistent.
Reproducibility Assessment of K-Means Clustering and Applications
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 135~144
DOI : 10.5351/KJAS.2004.17.1.135
We propose a reproducibility (validity) assessment procedure of K-means cluster analysis by randomly partitioning the data set into three parts, of which two subsets are used for developing clustering rules and one subset for testing consistency of clustering rules. Also, as an alternative to Rand index and corrected Rand index, we propose an entropy-based consistency measure between two clustering rules, and apply it to determination of the number of clusters in K-means clustering.
Misleading Confidence Interval for Sum of Variances Calculated by PROC MIXED of SAS
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 145~151
DOI : 10.5351/KJAS.2004.17.1.145
PROC MIXED fits a variety of mixed models to data and enables one to use these fitted models to make statistical inferences about the data. However, the simulation study in this article shows that PROC MIXED using REML estimators provides one with a confidence interval, that does not keep the stated confidence coefficients, on sums of two variance components in the simple regression model with unbalanced nested error structure which is a mixed model.
A Comparison of Multivariate R-Techniques in SAS, SPSS, Minitab and S-plus
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 153~164
DOI : 10.5351/KJAS.2004.17.1.153
In this study, we compare multivariate R-techniques in the up-to-date versions of SAS, SPSS, Minitab and S-plus. The direct input method by typing in command is considered for SAS, while the menu-driven method is considered for SPSS, Minitab and S-plus. Comparison was made in terms of input data format, input option, charts and outputs.
A Development of Multivariate Analysis System by Using Excel
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 165~172
DOI : 10.5351/KJAS.2004.17.1.165
Recently, there have been several studies to develop the multivariate data analysis system which can be readily used. The common characteristic of these studies is to develop the GUI system to which advanced statistical methods can be conveniently applied. In an extension of these studies, this study aims to supply users in various fields an interactive system with the convenience of the environment of GUI, which is constructed with the Excel macro and VBA, to apply multivariate data analysis methods easily. This system provides a graphic-oriented and menu-centered user interface in the Microsoft Excel which is widely used spreadsheet and analysis program.
Introduction of a Nonlinear Regression Analysis System NLIN2000
Korean Journal of Applied Statistics, volume 17, issue 1, 2004, Pages 173~184
DOI : 10.5351/KJAS.2004.17.1.173
A statistical software for nonlinear regression analysis, NLIN2000, is introduced. This software, operated tinder the Window systems, has many user-friendly functions and Provides various statistics. As an upgraded version of the Previous Program operated under the DOS system, NLIN2000 provides easier steps for model specification and fitting process than any other statistical packages. Also it has a database system for model functions which has addition and deletion options. While it can be a useful research tool for statisticians, NLIN2000 can be used practically also by researchers in many other scientific fields, who needs nonlinear regression analysis for their study