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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 20, Issue 3 - Nov 2007
Volume 20, Issue 2 - Jul 2007
Volume 20, Issue 1 - Mar 2007
Selecting the target year
Estimation for the Change of Daily Maxima Temperature
Ko, Wang-Kyung ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 1~9
DOI : 10.5351/KJAS.2007.20.1.001
This investigation on the change of the daily maxima temperature in Seoul, Daegu, Chunchen, Youngchen was triggered by news items such as the earth is getting warmer and a recent news item that said that Korea is getting warmer due to this climatic change. A statistical analysis on the daily maxima for June over this period in Seoul revealed a positive trend of 1.1190 centigrade over the 45 years, a change of 0.0249 degrees annually. Due to the large variation on these maximum temperatures, one can raise the question on the significance of this increase. To check the goodness of fit of the proposed extreme value model, we shown a Q-Q plot of the observed quantiles against the simulated quantiles and a probability plot. And we calculated statistics each month and a tolerance limit. This is tested through simulating a large number of similar datasets from an Extreme Value distribution which described the observed data very well. Only 0.02% of the simulated datasets showed an increase of this degrees or larger, meaning that the probability is very low for such an event to occur.
A New Method of Yielding the GDP of Korea Small Business: Conversion of the Statistics of Workplace Units to Industrial Units
Jeong, Hyeong-Chul ; Chung, Yeon-Seung ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 11~22
DOI : 10.5351/KJAS.2007.20.1.011
In this study, we have proposed the new statistical methods to convert the statistics based of workplace units into the statistics based of industrial units using the industrial survey data published by National Statistical Once in 2001. It could help to apprehend the weight of service sectors of korea small business in terms of the Gross Domestic Product (GDP).
A Strategy Through Segmentation Using Factor and Cluster Analysis: focusing on corporations having a special status
Cho, Yong-Jun ; Kim, Yeong-Hwa ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 23~38
DOI : 10.5351/KJAS.2007.20.1.023
Corporations adopt a segmentation depends on the existence of target variables, in general. In this paper, for the case of no target variables, a strategy through segmentation is proposed for corporations having a special status based on the management index. In case of segmentation using cluster analysis, however, if one classify according to many variables then he will be in face of difficulties in characterizing. Therefore, after extracting representative factors by factor analysis, a segmentation method through 2 step cluster analysis is employed on the basis of these representative factors. As a result, six segmentation groups are found and the resulting strategy is proposed which strengthens prominent factors and makes up defective factors for each group.
Analysis of Interval-censored Survival Data from Crossover Trials with Proportional Hazards Model
Kim, Eun-Young ; Song, Hae-Hiang ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 39~52
DOI : 10.5351/KJAS.2007.20.1.039
Crossover trials of new drugs in the treatment of angina pectoris, which frequently use treadmill exercise test for the assessment of its efficacy, produce censored survival times. In this paper we consider analysis approaches for censored survival times from crossover trials. Previously, a stratified Cox model for paired observation and nonparametric methods have been presented as possible analysis methods. On the other hand, the differences of two survival times would produce interval-censored survival times and we propose a Cox model for interval-censored data as n alternative analysis method. Example data is analyzed in order to compare these different methods.
Evidence of Integrated Heteroscedastic Processes for Korean Financial Time Series
Park, J.A. ; Baek, J.S. ; Hwang, S.Y. ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 53~60
DOI : 10.5351/KJAS.2007.20.1.053
Conditionally heteroscedastic time series models such as GARCH processes have frequently provided useful approximations to the real aspects of financial time series. It is not uncommon that financial time series exhibits near non-stationary, say, integrated phenomenon. For stationary GARCH processes, a shock to the current conditional variance will be exponentially converging to zero and thus asymptotically negligible for the future conditional variance. However, for the case of integrated process, the effect will remain for a long time, i.e., we have a persistent effect of a current shock on the future observations. We are here concerned with providing empirical evidences of persistent GARCH(1,1) for various fifteen domestic financial time series including KOSPI, KOSDAQ and won-dollar exchange rate. To this end, kurtosis and Integrated-GARCH(1,1) fits are reported for each data.
Information Theory and Data Visualization Approach to Poll Analysis
Huh, Moon-Yul ; Cha, Woon-Ock ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 61~78
DOI : 10.5351/KJAS.2007.20.1.061
A method for poll analysis using information theory and data visualization is proposed in this paper. Questions of opinion poll consist of a target variable and many explanation variables. The type of explanation variables is either numerical or categorical. In this study, explanation variables of mixed types have been ranked according to the magnitude of their effect on target variable by using mutual information. Likewise, the order of explanation variables has been evaluated using data visualization. This is the first study to quantify the impact of specific explanation variable on the related target variable.
Improving a Test for Normality Based on Kullback-Leibler Discrimination Information
Choi, Byung-Jin ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 79~89
DOI : 10.5351/KJAS.2007.20.1.079
A test for normality introduced by Arizono and Ohta(1989) is based on fullback-Leibler discrimination information. The test statistic is derived from the discrimination information estimated using sample entropy of Vasicek(1976) and the maximum likelihood estimator of the variance. However, these estimators are biased and so it is reasonable to make use of unbiased estimators to accurately estimate the discrimination information. In this paper, Arizono-Ohta test for normality is improved. The derived test statistic is based on the bias-corrected entropy estimator and the uniformly minimum variance unbiased estimator of the variance. The properties of the improved KL test are investigated and Monte Carlo simulation is performed for power comparison.
A Comparison on Forecasting Performance of STARMA and STBL Models with Application to Mumps Data
Lee, S.D. ; Lee, Y.J. ; Park, Y.S. ; Joo, J.S. ; Lee, K.M. ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 91~102
DOI : 10.5351/KJAS.2007.20.1.091
The major purpose of this article is to formulate a class of Space Time Autoregressive Moving Average(STARMA) model and Space Time Bilinear model(STBL), to discuss some of the their statistical properties such as model, identification approaches, some procedure for estimation and the predictions, and to compare the STARMA model with the STBL model. For illustration, The Mumps data reported from eight city & provinces monthly over the years 2001-2006 are used and the result from STARMA and STBL model are compared with using SSF(Sum of Square Prediction Error).
Small Sample Asymptotic Inferences for Autoregressive Coefficients via Saddlepoint Approximation
Na, Jong-Hwa ; Kim, Jeong-Sook ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 103~115
DOI : 10.5351/KJAS.2007.20.1.103
In this paper we studied the small sample asymptotic inference for the autoregressive coefficient in AR(1) model. Based on saddlepoint approximations to the distribution of quadratic forms, we suggest a new approximation to the distribution of the estimators of the noncircular autoregressive coefficients. Simulation results show that the suggested methods are very accurate even in the small sample sizes and extreme tail area.
A New Measure of Agreement to Resolve the Two Paradoxes of Cohen's Kappa
Park, Mi-Hee ; Park, Yong-Gyu ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 117~132
DOI : 10.5351/KJAS.2007.20.1.117
table showing binary agreement between two raters, it is known that Cohen's
, a chance-corrected measure of agreement, has two paradoxes.
is substantially sensitive to raters' classification probabilities(marginal probabilities) and does not satisfy conditions as a chance-corrected measure of agreement. However,
and other established measures have a reasonable and similar value when each marginal distribution is close to 0.5. The objectives of this paper are to present a new measure of agreement, H, which resolves paradoxes of
by adjusting unbalanced marginal distributions and to compare the proposed measure with established measures through some examples.
Sparse Design Problem in Local Linear Quasi-likelihood Estimator
Park, Dong-Ryeon ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 133~145
DOI : 10.5351/KJAS.2007.20.1.133
Local linear estimator has a number of advantages over the traditional kernel estimators. The better performance near boundaries is one of them. However, local linear estimator can produce erratic result in sparse regions in the realization of the design and to solve this problem much research has been done. Local linear quasi-likelihood estimator has many common properties with local linear estimator, and it turns out that sparse design can also lead local linear quasi-likelihood estimator to erratic behavior in practice. Several methods to solve this problem are proposed and their finite sample properties are compared by the simulation study.
Efficient Edge Detection in Noisy Images using Robust Rank-Order Test
Lim, Dong-Hoon ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 147~157
DOI : 10.5351/KJAS.2007.20.1.147
Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a
window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.
Critical Review of Statistics Chapter in High School Mathematics I
Huh, Myung-Hoe ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 159~165
DOI : 10.5351/KJAS.2007.20.1.159
The statistics chapter in High School Mathematics I as implemented in The 7th Curriculum is reviewed critically. In views from mathematical integrity or logic, the current contents are not satisfactory in several key issues. Specific instances are the law of large numbers, normal distribution and confidence intervals for population mean. We suggest alternative teaching points to handle such difficulties and propose re-structuring the course syllabus with reduced items.
Comparison of the Cluster Validation Methods for High-dimensional (Gene Expression) Data
Jeong, Yun-Kyoung ; Baek, Jang-Sun ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 167~181
DOI : 10.5351/KJAS.2007.20.1.167
Many clustering algorithms and cluster validation techniques for high-dimensional gene expression data have been suggested. The evaluations of these cluster validation techniques have, however, seldom been implemented. In this paper we compared various cluster validity indices for low-dimensional simulation data and real gene expression data, and found that Dunn's index is the most effective and robust, Silhouette index is next and Davies-Bouldin index is the bottom among the internal measures. Jaccard index is much more effective than Goodman-Kruskal index and adjusted Rand index among the external measures.
Sample Size Determination for Comparing Tail Probabilities
Lee, Ji-An ; Song, Hae-Hiang ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 183~194
DOI : 10.5351/KJAS.2007.20.1.183
The problem of calculating the sample sizes for comparing two independent binomial proportions is studied, when one of two probabilities or both are smaller than 0.05. The use of Whittemore(1981)'s corrected sample size formula for small response probability, which is derived based oB multiple logistic regression, demonstrates much larger sample sizes compared to those by the asymptotic normal method, which is derived for the comparison of response probabilities belonging to the normal range. Therefore, applied statisticians need to be careful in sample size determination with small response probability to ensure intended power during a planning stage of clinical trials. The results of this study describe that the use of the sample size formula in the textbooks might sometimes be risky.
Graphical Method for Multiple Regression Model
Lee, W.R. ; Lee, U.K. ; Hong, C.S. ;
Korean Journal of Applied Statistics, volume 20, issue 1, 2007, Pages 195~204
DOI : 10.5351/KJAS.2007.20.1.195
In order to represent multiple regression data, an alternative graphical method, called as SSR Plot, is proposed by using geometrical description methods. This plot uses the relation that the sum of sqaures for regression (SSR) of two explanatory variables is known as the sum of the SSR of one variable and the increase in the SSR due to the addition of other variable to the model that already contains a variable. This half circle shaped SSR plot contains vectors corresponding explanatory variables. We might conclude that some explanatory variables corresponding to vectors which locate near the horisontal axis do affect the response variable. Also, for the regression model with two explanatory variables, a magnitude of the angle between two vectors can be identified for suppression.