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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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The Analysis of the Number of Donations Based on a Mixture of Poisson Regression Model
Kim In-Young ; Park Su-Bum ; Kim Byung-Soo ; Park Tae-Kyu ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 1~12
DOI : 10.5351/KJAS.2006.19.1.001
The aim of this study is to analyse a survey data on the number of charitable donations using a mixture of two Poisson regression models. The survey was conducted in 2002 by Volunteer 21, an nonprofit organization, based on Koreans, who were older than 20. The mixture of two Poisson distributions is used to model the number of donations based on the empirical distribution of the data. The mixture of two Poisson distributions implies the whole population is subdivided into two groups, one with lesser number of donations and the other with larger number of donations. We fit the mixture of Poisson regression models on the number of donations to identify significant covariates. The expectation-maximization algorithm is employed to estimate the parameters. We computed 95% bootstrap confidence interval based on bias-corrected and accelerated method and used then for selecting significant explanatory variables. As a result, the income variable with four categories and the volunteering variable (1: experience of volunteering, 0: otherwise) turned out to be significant with the positive regression coefficients both in the lesser and the larger donation groups. However, the regression coefficients in the lesser donation group were larger than those in larger donation group.
A Review of Cluster Analysis for Time Course Microarray Data
Sohn In-Suk ; Lee Jae-Won ; Kim Seo-Young ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 13~32
DOI : 10.5351/KJAS.2006.19.1.013
Biologists are attempting to group genes based on the temporal pattern of gene expression levels. So far, a number of methods have been proposed for clustering microarray data. However, the results of clustering depends on the genes selection, therefore the gene selection with significant expression difference is also very important to cluster for microarray data. Thus, this paper present the results of broad comparative studies to time course microarray data by considering methods of gene selection, clustering and cluster validation.
Comparison of a Class of Nonlinear Time Series models (GARCH, IGARCH, EGARCH)
Kim S.Y. ; Lee Y.H. ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 33~41
DOI : 10.5351/KJAS.2006.19.1.033
In this paper, we analyse the volatilities in financial data such as stock prices and exchange rates in term of a class of nonlinear time series models. We compare the performance of Generalized Autoregressive Conditional Heteroscadastic(GARCH) , Integrated GARCH(IGARCH), Exponential GARCH(EGARCH) models by KOSPI (Korean stock Prices Index) data. The estimation for the parameters in the models was carried out by the ML methods.
Hybrid Computing Method for Customer Satisfaction Index
Cho Yong-Jun ; Kim Yeong-Hwa ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 43~55
DOI : 10.5351/KJAS.2006.19.1.043
CS(Customer Satisfaction) has been focused as one of the most important factors in business administration nowadays. After measuring and evaluating CS level, most companies are performing many activities to improve it. Therefore, it is very important for driving CS management to measure the exact CS level. When measuring CS level, however, CSI(Customer Satisfaction Index) is changed by the computing method of importance for CS factors, and the corporate strategy is changed by CSI. In this research, some computing methods are reviewed and compared through the analysis of real data. Also, a hybrid computing method for CSI is proposed and compared it with other methods.
Missing Imputation Methods Using the Spatial Variable in Sample Survey
Lee Jin-Hee ; Kim Jin ; Lee Kee-Jae ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 57~67
DOI : 10.5351/KJAS.2006.19.1.057
In sampling survey, nonresponse tend to occur inevitably. If we use information from respondents only, the estimates will be baised. To overcome this, various non-response imputation methods have been studied. If there are few auxiliary variables for replacing missing imputation or spatial autocorrelation exists between respondents and nonrespondents, spatial autocorrelation can be used for missing imputation. In this paper, we apply several nonresponse imputation methods including spatial imputation for the analysis of farm household economy data of the Gangwon-Do in 2002 as an example. We show that spatial imputation is more efficient than other methods through the numerical simulations.
A Study on the Randomized Response Technique by PPS Sampling
Lee Gi-Sung ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 69~80
DOI : 10.5351/KJAS.2006.19.1.069
In this study, we make an effort to find a method to acquire sensitive information when sensitive populations are consisted of several clusters that vary in size. We suggest and systemize the theoretical validity for applying RRT(Randomized Response Technique) to PPS(Probability Proportional to Size) sampling method and derive the estimate and it`s variance of the proportion of sensitive characteristic of population by using the suggested method. We compare the efficiency of the suggested technique by two-stage equal probability sampling. We examine practical aspects of the suggested method of RRT by PPS sampling through field survey.
A Control Chart Method Using Quartiles for Asymmetric Distributed Processes
Park Sung-Hyun ; Park Hee-Jin ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 81~96
DOI : 10.5351/KJAS.2006.19.1.081
This paper proposes a simple control chart method which can be practically used for asymmetric process data where the distribution is unknown. If we use the Shewhart type control charts which are based on normality assumption for the asymmetric process data, the type I error could increase as the asymmetry increases and the effectiveness of control chart to control variation decreases. To solve such problems, this paper suggests to calculate the control limits based on the quartiles. If we obtain the control limits by such quartile method, the type I error could decrease and it looks much more practical for asymmetric distributed process data.
On Confidence Intervals of Robust Regression Estimators
Lee Dong-Hee ; Park You-Sung ; Kim Kee-Whan ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 97~110
DOI : 10.5351/KJAS.2006.19.1.097
Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.
Rank Transformation Technique in a Two-stage Two-level Balanced Nested Design
Choi Young-Hun ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 111~120
DOI : 10.5351/KJAS.2006.19.1.111
In a two-stage two-level balanced nested design, type I error rates for the parametric tests and the rank transformed tests for the main effects and the nested effects are in overall similar to each other. Furthermore, powers for the rank transformed statistic for the main effects and the nested effects in a two-stage two-level balanced nested design are generally superior to powers for the parametric statistic When the effect size and the sample size are increased, we can find that powers increase for the parametric statistic and the rank transformed statistic are dramatically improved. Especially for the case of the fixed effects in the asymmetric distributions such as an exponential distribution, powers for the rank transformed tests are quite high rather than powers for the parametric tests.
Resampling Methods on Frequency Domains for Time Series
Yeo In-Kwon ; Yoon Wha-Hyung ; Cho Sin-Sup ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 121~134
DOI : 10.5351/KJAS.2006.19.1.121
This paper presents the resampling method for time series data in the frequency domain obtained by using discrete cosine transforms(DCT) The advantage of the proposed method is to generate bootstrap samples in time domain comparing with existing bootstrapping method. When time series are stationary, statistical properties of DCT coefficients are investigated and provide the verification of the proposed procedure.
Predicting Unknown Composition of a Mixture Using Independent Component Analysis
Lee Hye-Seon ; Song Jae-Kee ; Park Hae-Sang ; Jun Chi-Hyuck ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 135~148
DOI : 10.5351/KJAS.2006.19.1.135
Independent component analysis (ICA) is a statistical method for transforming an observed high-dimensional multivariate data into statistically independent components. ICA has been applied increasingly in wide fields of spectrum application since ICA is able to extract unknown components of a mixture from spectra. We focus on application of ICA for separating independent sources and predicting each composition using extracted components. The theory of ICA is introduced and an application to a metal surface spectra data will be described, where subsequent analysis using non-negative least square method is performed to predict composition ratio of each sample. Furthermore, some simulation experiments are performed to demonstrate the performance of the proposed approach.
Ordinal Variable Selection in Decision Trees
Kim Hyun-Joong ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 149~161
DOI : 10.5351/KJAS.2006.19.1.149
The most important component in decision tree algorithm is the rule for split variable selection. Many earlier algorithms such as CART and C4.5 use greedy search algorithm for variable selection. Recently, many methods were developed to cope with the weakness of greedy search algorithm. Most algorithms have different selection criteria depending on the type of variables: continuous or nominal. However, ordinal type variables are usually treated as continuous ones. This approach did not cause any trouble for the methods using greedy search algorithm. However, it may cause problems for the newer algorithms because they use statistical methods valid for continuous or nominal types only. In this paper, we propose a ordinal variable selection method that uses Cramer-von Mises testing procedure. We performed comparisons among CART, C4.5, QUEST, CRUISE, and the new method. It was shown that the new method has a good variable selection power for ordinal type variables.
Risk Difference, Relative Risk, and Odds Ratio: A Graphic Approach
Cho Tae-Kyoung ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 163~170
DOI : 10.5351/KJAS.2006.19.1.163
The argument concerning the choice of effect measure for epidemiologic data or clinic data has been renewed. But the relationships among effect measures can be confusing if effect measures are expressed by conventional mathematical functions alone. In this article, risk difference(RD), relative risk(RR), and odds ratios(OR) for binary data are presented by radar diagram instead of mathematical functions and the relationships among them are showed using radar diagram. This radar diagram is offered flexible conceptual tool to understand effect measures, DR, RR, and OR for binary data.
The Weighted Polya Posterior Confidence Interval For the Difference Between Two Independent Proportions
Lee Seung-Chun ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 171~181
DOI : 10.5351/KJAS.2006.19.1.171
The Wald confidence interval has been considered as a standard method for the difference of proportions. However, the erratic behavior of the coverage probability of the Wald confidence interval is recognized in various literatures. Various alternatives have been proposed. Among them, Agresti-Caffo confidence interval has gained the reputation because of its simplicity and fairly good performance in terms of coverage probability. It is known however, that the Agresti-Caffo confidence interval is conservative. In this note, a confidence interval is developed using the weighted Polya posterior which was employed to obtain a confidence interval for the binomial proportion in Lee(2005). The resulting confidence interval is simple and effective in various respects such as the closeness of the average coverage probability to the nominal confidence level, the average expected length and the mean absolute error of the coverage probability. Practically it can be used for the interval estimation of the difference of proportions for any sample sizes and parameter values.
Comparison Studies of Classification Methods based on L
-Distance and L
Baek Soo-Jin ; Hwang Jin-Soo ; Kim Jean-Kyung ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 183~193
DOI : 10.5351/KJAS.2006.19.1.183
We consider a new classification method(DnDclass) combining two classification rules based on
-data depth(L1DDclass). To investigate characteristics and to evaluate the performance of these classification methods, we use simulation data in various settings. Through this simulation study, we can confirm that the new method, DnDclass, performs relatively well in many cases.
Golden Ratio and Human Body
Jang Dae-Heung ;
Korean Journal of Applied Statistics, volume 19, issue 1, 2006, Pages 195~201
DOI : 10.5351/KJAS.2006.19.1.195
We tested that height/navel height ratio of Pukyong national university students is the same as golden ratio and compared height/navel height ratio of Pukyong national university students with height/navel height ratio of American university students.