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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 19, Issue 3 - Nov 2006
Volume 19, Issue 2 - Jul 2006
Volume 19, Issue 1 - Mar 2006
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A Study on Men`s 8-Constitutional Characteristics Using the Oneway Analysis of Variance
Rhee Sang-Beom ; Park Young-Bae ; Choi Kyung-Mee ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 203~215
DOI : 10.5351/KJAS.2006.19.2.203
In Oriental Medicine, there have been a number of researches in 8-Constitution medicine which classifies human bodies into one of 8 categories. Since the diagnosis of 8-Constitution depending on pulse types is often subjective, standardization of the diagnosis and therapy requires objective characteristics of 8 constitutions. A questionnaire of 80 items about personal symptoms were given to patients while they were classified into one of 8 constitutions based on their pulse types and responses to constitution-based acupuncture therapy. One-way analysis of variance and Duncan`s multiple comparison test were used to verify the significant items. Most of the significant items in this study coincided with supposed-to-be clinical characteristics of 8-constitutions.
Confidence Intervals for a tow Binomial Proportion
Ryu Jae-Bok ; Lee Seung-Joo ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 217~230
DOI : 10.5351/KJAS.2006.19.2.217
e discuss proper confidence intervals for interval estimation of a low binomial proportion. A large sample surveys are practically executed to find rates of rare diseases, specified industrial disaster, and parasitic infection. Under the conditions of 0 < p
0.1 and large n, we compared 6 confidence intervals with mean coverage probability, root mean square error and mean expected widths to search a good one for interval estimation of population proportion p. As a result of comparisons, Mid-p confidence interval is best and AC, score and Jeffreys confidence intervals are next.
A Statistical Approach to Paired versus Group Comparisons
Kim Tae-Min ; Kim Sang-Boo ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 231~240
DOI : 10.5351/KJAS.2006.19.2.231
It is well understood that a paired comparison (paired t test) provides better precision than a group comparison (two-sample t test), when the pairing is effective (the variation within a pair is small). However, when the variation among the pairs is sufficiently small, the group comparison is likely to yield a better result. To get a statistical explanation of this, we examine the two methods through an analogy to one-way and two-way analysis of variance. We introduce a new measure, R statistic, which is the ratio of their confidence interval lengths, as a quantitative criterion for comparing the two methods. The distribution of the Rf statistic is described by t and F distribution functions. Through this characterization, we show that the paired comparison can be better than group comparison when the variation among the pairs is statistically significantly large.
Testing Multivariate Normality Based on EDF Statistics
Kim Nam-Hyun ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 241~256
DOI : 10.5351/KJAS.2006.19.2.241
We generalize the
-von Mises Statistic to test multivariate normality using Roy`s union-intersection principle. We show the limit distribution of the suggested statistic is representable as the integral of a suitable Gaussian process. We also consider the computational aspects of the proposed statistic. Power performance is assessed in a Monte Carlo study.
Statistical Properties of Second Type Central Composite Designs
Kim Hyuk-Joo ; Park Sung-Hyun ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 257~270
DOI : 10.5351/KJAS.2006.19.2.257
Kim(2002) proposed a second type of central composite design in which the positionsof the axial points are indicated by two numbers, and called it CCD2. In the present paper, we have studied CCD2 further and obtained several new facts. We have obtained CCD2`s that have both orthogonality and rotatability, both orthogonality and slope rotatability, and both rotatability and uniform precision. We also have applied Park and Kim`s (1992) measure of slope rotatability to such CCD2`s and observed some useful results.
Tree-structured Clustering for Mixed Data
Yang Kyung-Sook ; Huh Myung-Hoe ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 271~282
DOI : 10.5351/KJAS.2006.19.2.271
The aim of this study is to propose a tree-structured clustering for mixed data. We suggest a scaling method to reduce the variable selection bias among categorical variables. In numerical examples such as credit data, German credit data, we note several differences between tree-structured clustering and K-means clustering.
Cho Ki-Jong ; Jeong Seok-Oh ; Shin Key-Il ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 283~290
DOI : 10.5351/KJAS.2006.19.2.283
Generally speaking, power transformations such as Box-Cox transformation(1964) is applied for variance stabilization and symmetry. But, when the distribution of the original data has a large mean with a small variance or the coefficient of variation is very small, they don`t work at all. This paper propose a simple method to introduce a shift parameter before applying power transformations and showed the numerical evidence by Monte Carlo simulation and a real data analysis.
A Study on the Data Fusion Method using Decision Rule for Data Enrichment
Kim S.Y. ; Chung S.S. ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 291~303
DOI : 10.5351/KJAS.2006.19.2.291
Data mining is the work to extract information from existing data file. So, the one of best important thing in data mining process is the quality of data to be used. In this thesis, we propose the data fusion technique using decision rule for data enrichment that one phase to improve data quality in KDD process. Simulations were performed to compare the proposed data fusion technique with the existing techniques. As a result, our data fusion technique using decision rule is characterized with low MSE or misclassification rate in fusion variables.
Outlier Detection of Autoregressive Models Using Robust Regression Estimators
Lee Dong-Hee ; Park You-Sung ; Kim Kee-Whan ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 305~317
DOI : 10.5351/KJAS.2006.19.2.305
Outliers adversely affect model identification, parameter estimation, and forecast in time series data. In particular, when outliers consist of a patch of additive outliers, the current outlier detection procedures suffer from the masking and swamping effects which make them inefficient. In this paper, we propose new outlier detection procedure based on high breakdown estimators, called as the dual robust filtering. Empirical and simulation studies in the autoregressive model with orders p show that the proposed procedure is effective.
Hierarchical Smoothing Technique by Empirical Mode Decomposition
Kim Dong-Hoh ; Oh Hee-Seok ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 319~330
DOI : 10.5351/KJAS.2006.19.2.319
A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.
Shrinkage Solution of Quantification Method III
Huh Myung-Hoe ; Lee Yong-Goo ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 331~338
DOI : 10.5351/KJAS.2006.19.2.331
Quantification method III is designed by C. Hayashi as visualizing technique for two-way cross-classified tables. Specially in Japan, its usefulness is timely proven in social and marketing surveys. In several instances, relatively large quantification scores are assigned to low-frequency categories. Thus, they lead to unreliable data interpretation. The aim of this study is to develop stable solution to overcome such traits of quantification method III. The solution is of shrinkage type induced by small perturbations and is applied to a multiple response data obtained in a Korean social survey.
Two Bootstrap Confidence Intervals of Ridge Regression Estimators in Mixture Experiments
Jang Dae-Heung ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 339~347
DOI : 10.5351/KJAS.2006.19.2.339
In mixture experiments, performing experiments in highly constrained regions causes collinearity problems. We can use the ridge regression as a means for stabilizing the coefficient estimators in the fitted model. But there is no theory available on which to base statistical inference of ridge estimators. The bootstrap technique could be used to seek the confidence intervals for ridge estimators.
Interval Estimation in Mixed Model by Use of PROC MIXED
Park Dong-Joon ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 349~360
DOI : 10.5351/KJAS.2006.19.2.349
PROC MIXED in SAS can be utilized to make inferences on parameters in a mixed model by use of Restricted Maximum Likelihood Estimation Method or Maximum Likelihood Estimation Method which has more merits than ANOVA method. A regression model with unbalanced nested error structure that belongs to a mixed model is used to construct confidence intervals on variances among groups, within groups, and regression coefficients in the model. PROC MIXED is applied to three different sample sizes for simulation. As a result of the simulation study, PROC MIXED generates confidence intervals on parameters that maintain the stated confidence coefficient in a large sample size. However, it does not generate confidence intervals that maintain the stated confidence coefficient for variance components among groups and intercept in a small sample size.
Applications of Diamond Graph
Hong C.S. ; Ko Y.S. ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 361~368
DOI : 10.5351/KJAS.2006.19.2.361
There are lots of two and three dimensional graph representing two dimensional categorical data. Among them, Li, et al. (2003) proposed Diamond Graph that projects three dimensional graph into two dimension whereby the third dimension is replaced with a diamond shape whose area and middle and vertical and horizontal lengths represent the outcome. In this paper, we use the Diamond graph to test the independence of two predictor variables for two dimensional data. And this graph could be applied for finding the best fitted log-linear model to three dimensional data.
A Study on Variance Change Point Detection for Time Series Data in Progress
Choi Hyun-Seok ; Kang Hoon-Kyu ; Song Gyu-Moon ; Kim Tae-Yoon ;
Korean Journal of Applied Statistics, volume 19, issue 2, 2006, Pages 369~377
DOI : 10.5351/KJAS.2006.19.2.369
This paper considers moving variance ratio (MVR) for valiance detection problem with time series data in progress. For testing purpose, parametric method based on F distribution and nonparametric method based on empirical distribution are compared via simulation study.