Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Korean Journal of Applied Statistics
Journal Basic Information
Journal DOI :
The Korean Statistical Society
Editor in Chief :
Volume & Issues
Volume 22, Issue 6 - Dec 2009
Volume 22, Issue 5 - Oct 2009
Volume 22, Issue 4 - Aug 2009
Volume 22, Issue 3 - Jun 2009
Volume 22, Issue 2 - Apr 2009
Volume 22, Issue 1 - Feb 2009
Selecting the target year
Modified Test Statistic for Identity of Two Distribution on Credit Evaluation
Hong, C.S. ; Park, H.S. ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 237~248
DOI : 10.5351/KJAS.2009.22.2.237
The probability of default on the credit evaluation study is represented as a linear combination of two distributions of default and non-default, and the distribution of the probability of default are generally known in most cases. Except the well-known Kolmogorov-Smirnov statistic for testing the identity of two distribution, Kuiper, Cramer-Von Mises, Anderson-Darling, and Watson test statistics are introduced in this work. Under the assumption that the population distribution is known, modified Cramer-Von Mises, Anderson-Darling, and Watson statistics are proposed. Based on score data generated from various probability density functions of the probability of default, the modified test statistics are discussed and compared.
The Term Structure and Predicting the Domestic Recessions
Kim, Tae-Ho ; Song, Dae-Sub ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 249~260
DOI : 10.5351/KJAS.2009.22.2.249
Various methods have been suggested in developing the useful leading indicators to predict the actual realizations when time laps exist between policy plannings and future events. The recent economic crisis could have been relived if the information necessary to respond to the future evolutionary process is provided in advance. As the relations between the financial variables and the real economic activity become unstable because of the changes in the financial environment, this study attempts to estimate the capabilities of various internal and external term spreads in predicting the future business trend, followed by comparison and evaluation.
Assessments for MGARCH Models Using Back-Testing: Case Study
Hwang, S.Y. ; Choi, M.S. ; Do, J.D. ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 261~270
DOI : 10.5351/KJAS.2009.22.2.261
Current financial crisis triggered by shaky U.S. banking system adds to the emphasis on the importance of the volatility in controlling and understanding financial time series data. The ARCH and GARCH models have been useful in analyzing economic time series volatilities. In particular, multivariate GARCH(MGARCH, for short) provides both volatilities and conditional correlations between several time series and these are in turn applied to computations of hedge-ratio and VaR. In this short article, we try to assess various MGARCH models with respect to the back-testing performances in VaR study. To this end, 14 korean stock prices are analyzed and it is found that MGARCH outperforms rolling window, and BEKK and CCC are relatively conservative in back-testing performance.
Fitting Bivariate Generalized Binomial Models of the Sarmanov Type
Lee, Joo-Yong ; Kim, Kee-Young ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 271~280
DOI : 10.5351/KJAS.2009.22.2.271
For bivariate binomial data with both intra and inter-class correlation, Danaher and Hardie (2005) proposed a bivariate beta-binomial model. However, the model is limited to the situation where the intra-class correlation is strictly positive. Thus it might be seriously inadequate for data with a negative intra-class correlation. Several authors have considered generalized binomial distributions covering a wider range of intra-class correlation which could relax the possible model restrictions imposed. Among others there are the additive/multiplicative and the beta/extended beta binomial model. In this study, bivariate models of the Sarmanov (1966) type are formed by combining each of those univariate models to take care of the inter-class correlation, and are evaluated in terms of the goodness-of-fit. As a result, B-mB and B-ebB are fitted, successfully, to real data and that B-mB, which has a wider permissible range than B-ebB for the intra-class correlation is relatively preferred.
A Study on the Satisfaction of Self-Employed
Oh, Yu-Jin ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 281~296
DOI : 10.5351/KJAS.2009.22.2.281
This study examines the job and life satisfactions of the self-employed. It uses the Korean Labour and Income Panel Study(KLIPS, hereafter) data for 1998 and 2004. We examine the phases of satisfaction and what variables influence satisfaction for both years and compare the results in order to see what changed between the two regimes. We make use of k-means clustering to divide self-employed into similar degrees of satisfaction. As a result, we are able to classify the self-employed into three groups(low, medium and high) both for the two regimes. High groups consists of relatively younger, well-educated, low working dates, higher proportion of woman than other groups. As a result of regression analysis, we have some evidence that women are more satisfied than men for job satisfaction and that the existence of income is more important than the amount of income for life satisfaction. The age, education, satisfaction for working place, and health are significant to both satisfactions.
Analysis of Stress level of Korean Household Members due to Household Debt
Oh, Man-Suk ; Hyun, Seung-Me ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 297~307
DOI : 10.5351/KJAS.2009.22.2.297
Korean household debt is one of the main sources of the current financial crisis. This paper studies the impact of household members' attributes such as a type of housing(self-own or rent), education, age, average monthly income of the head of household, and the area of residence, on the stress level of the household members due to household debt. We analyze a real data set collected by KB Kookmin Bank in 2004. We consider low and high stress level as a binary response variable and use a logistic regression model with the attributes of household members as explanatory variables. A simple but well-fitting model is selected by backward elimination method based on the likelihood statistic for goodness-of-fit test, and the impact of the attributes on the stress level is studied from parameter estimates of the selected model. We also perform the similar analysis on a binary response variable which distinguishes households with no debt from the rest. From the analysis, the stress level tends to be low for households with self-own houses, high average monthly income, low education level, and young members.
A Consideration about Online Ratings in Internet Shopping Malls
Jang, Dae-Heung ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 309~315
DOI : 10.5351/KJAS.2009.22.2.309
The degree of the impression about a special commodity in the internet shopping malls depends on the evaluation and the corresponding rating of customers who purchased and used this commodity. We can find the problems in online ratings system of Korean internet shopping malls and suggest the simple solutions.
The Necessity of Independent Data Monitoring Committee in Domestic Clinical Trials
Kang, Seung-Ho ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 317~327
DOI : 10.5351/KJAS.2009.22.2.317
In adaptive designs important components of clinical trials may be changed based on the results of interim analysis. Several international guidelines point out that such interim analysis should be performed by independent experts who do not participate in clinical trials when adaptive designs are used in therapeutic confirmatory clinical trials, and if not, it may cause bias. The international guidelines recommend the establishment of independent data monitoring committee for conducting interim analysis independently.
Comparison of Methods for Linkage Analysis of Affected Sibship Data
Go, Min-Jin ; Lim, Kil-Seob ; Lee, Hak-Bae ; Song, Ki-Jun ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 329~340
DOI : 10.5351/KJAS.2009.22.2.329
For complex diseases such as diabetes, hypertension, it is believed that model-free methods might work better because they do not require a precise knowledge of the mode of inheritance controlling the disease trait. This is done by estimating the sharing probabilities that a pair shares zero, one, or two alleles identical by descent(IBD) and has some specific branches of test procedure, i.e., the mean test, the proportion test, and the minmax test. Among them, the minmax test is known to be more robust than others regardless of genetic mode of inheritance in current use. In this study, we compared the power of the methods which are based on minmax test and considering weighting schemes for sib-pairs to analyze sibship data. In simulation result, we found that the method based on Suarez' was more powerful than any others without respect to marker allele frequency, genetic mode of inheritance, sibship size. Also, The power of both Suarez- and Hodge-based methods was higher when marker allele frequency and sibship size were higher, and this result was remarkable in dominant mode of inheritance especially.
Determination of Sample Sizes of Bivariate Efficacy and Safety Outcomes
Lee, Hyun-Hak ; Song, Hae-Hiang ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 341~353
DOI : 10.5351/KJAS.2009.22.2.341
We consider sample-size determination problem motivated by comparative clinical trials where patient outcomes are characterized by a bivariate outcome of efficacy and safety. Thall and Cheng (1999) presented a sample size methodology for the case of bivariate binary outcomes. We propose a bivariate Wilcoxon-Mann-Whitney(WMW) statistics for sample-size determination for binary outcomes, and this nonparametric method can be equally used to determine sample sizes of ordinal outcomes. The two methods of sample size determination rely on the same testing strategy for the target parameters but differs in the test statistics, an asymptotic bivariate normal statistic of the transformed proportions in Thall and Cheng (1999) and nonparametric bivariate WMW statistic in the other method. Sample sizes are calculated for the two experimental oncology trials, described in Thall and Cheng (1999), and for the first trial example the sample sizes of a bivariate WMW statistic are smaller than those of Thall and Cheng (1999), while for the second trial example the reverse is true.
Confidence Interval for the Difference or Ratio of Two Median Failure Times from Clustered Survival Data
Lee, Seung-Yeoun ; Jung, Sin-Ho ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 355~364
DOI : 10.5351/KJAS.2009.22.2.355
A simple method is proposed for constructing nonparametric confidence intervals for the difference or ratio of two median failure times. The method applies when clustered survival data with censoring is randomized either (I) under cluster randomization or (II) subunit randomization. This method is simple to calculate and is based on non-parametric density estimation. The proposed method is illustrated with the otology study data and HL-A antigen study data. Moreover, the simulation results are reported for practical sample sizes.
Heterogeneity Analysis of the Male Birth Ratio Data
Lim, Hwa-Kyung ; Song, Seuck-Heun ; Song, Ju-Won ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 365~373
DOI : 10.5351/KJAS.2009.22.2.365
Since 1990, identifying the sex of fetus and illegal abortion has brought the sex ratio imbalance at birth in Korea due to a notion of preferring a son to a daughter, socio-economic development, population policy, and so forth. Although there have been many researches such as time series analysis and region difference analysis to monitor this sex ratio imbalance, they have a defect that time and space could not be included in the analysis simultaneously. This study analyzes the sex ratio imbalance at birth, taking into account time and region at the same time. The analysis considered the numbers of male and female babies, who were born as the third or latter in their families, in 2000 and 2001 at 234 Gu / Si / Goon administrative districts. Here, we suggest a mixture model of binomial distributions, assuming heterogeneous populations. The estimation of the location parameters, weights and correlation coefficient of the mixture model is conducted by the EM algorithm, and the heterogeneity of the regions is expressed as a picture using ArcView GIS.
Systematic Bias of Telephone Surveys: Meta Analysis of 2007 Presidential Election Polls
Kim, Se-Yong ; Huh, Myung-Hoe ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 375~385
DOI : 10.5351/KJAS.2009.22.2.375
For 2007 Korea presidential election, most polls by telephone surveys indicated Lee Myung-Bak led the second runner-up Jung Dong-Young by certain margin. The margin between two candidates can be estimated accurately by averaging individual poll results, provided there exists no systematic bias in telephone surveys. Most Korean telephone surveys via telephone directory are based on quota samples, with the region, the gender and the age-band as quota variables. Thus the surveys may result in certain systematic bias due to unbalanced factors inherent in quota sampling. The aim of this study is to answer the following questions by the analytic methods adopted in Huh et al. (2004): Question 1. Wasn't there systematic bias in estimates of support rates. Question 2. If yes, what was the source of the bias? To answer the questions, we collected eighteen surveys administered during the election campaign period and applied the iterated proportional weighting (the rim weighting) to the last eleven surveys to obtain the balance in five factors - region, gender, age, occupation and education level. We found that the support rate of Lee Myung-Bak was over-estimated consistently by 1.4%P and that of Jung Dong-Young was underestimated by 0.6%P, resulting in the over-estimation of the margin by 2.0%P. By investigating the Lee Myung-Bak bias with logistic regression models, we conclude that it originated from the under-representation of less educated class and/or the over-representation of house wives in telephone samples.
A General Class of Estimators of the Population Mean in Survey Sampling Using Auxiliary Information with Sub Sampling the Non-Respondents
Singh, Housila P. ; Kumar, Sunil ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 387~402
DOI : 10.5351/KJAS.2009.22.2.387
In this paper we have considered the problem of estimating the population mean
of the study variable y using auxiliary information in presence of non-response. Classes of estimators for
in the presence of non-response on the study variable y only and complete response on the auxiliary variable x is available, have been proposed in different situations viz., (i) population mean
is known, (ii) when population mean
are known; (iii) when population mean
is not known: and (iv) when both population mean
are not known: single and two-phase (or double) sampling. It has been shown that various estimators including usual unbiased estimator and the estimators reported by Rao (1986), Khare and Srivastava (1993, 1995) and Tabasum and Khan (2006) are members of the proposed classes of estimators. The optimum values of the first phase sample size n', second phase sample size n and the sub sampling fraction 1/k have been obtained for the fixed cost and the fixed precision. To illustrate foregoing, we have carried out an empirical investigation to reflect the relative performance of all the potentially competing estimators including the one due to Hansen and Hurwitz (1946) estimator, Rao (1986) estimator, Khare and Srivastava (1993, 1995) and Tabasum and Khan (2006) estimator.
A Small Area Estimation for Monthly Wage Using Mean Squared Percentage Error
Hwang, Hee-Jin ; Shin, Key-Il ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 403~414
DOI : 10.5351/KJAS.2009.22.2.403
Many researches have been devoted to the small area estimation related with the area level statistics. Almost all of the small area estimation methods are derived based on minimization of mean squared error(MSE). Recently Hwang and Shin (2008) suggested an alternative small area estimation method by minimizing mean squared percentage error. In this paper we apply this small area estimation method to the labor statistics, especially monthly wages by a branch area of labor department. The Monthly Labor Survey data (2007) is used for analysis and comparison of these methods.
Use of Minimal Spanning Trees on Self-Organizing Maps
Jang, Yoo-Jin ; Huh, Myung-Hoe ; Park, Mi-Ra ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 415~424
DOI : 10.5351/KJAS.2009.22.2.415
As one of the unsupervised learning neural network methods, self-organizing maps(SOM) are applied to various fields. It reduces the dimension of multidimensional data by representing observations on the low dimensional manifold. On the other hand, the minimal spanning tree(MST) of a graph that achieves the most economic subset of edges connecting all components by a single open loop. In this study, we apply the MST technique to SOM with subnodes. We propose SOM's with embedded MST and a distance measure for optimum choice of the size and shape of the map. We demonstrate the method with Fisher's Iris data and a real gene expression data. Simulated data sets are also analyzed to check the validity of the proposed method.
Bayesian Spatial Modeling of Precipitation Data
Heo, Tae-Young ; Park, Man-Sik ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 425~433
DOI : 10.5351/KJAS.2009.22.2.425
Spatial models suitable for describing the evolving random fields in climate and environmental systems have been developed by many researchers. In general, rainfall in South Korea is highly variable in intensity and amount across space. This study characterizes the monthly and regional variation of rainfall fields using the spatial modeling. The main objective of this research is spatial prediction with the Bayesian hierarchical modeling (kriging) in order to further our understanding of water resources over space. We use the Bayesian approach in order to estimate the parameters and produce more reliable prediction. The Bayesian kriging also provides a promising solution for analyzing and predicting rainfall data.
Multifactor Dimensionality Reduction(MDR) Analysis by Dummy Variables
Lee, Jea-Young ; Lee, Ho-Guen ;
Korean Journal of Applied Statistics, volume 22, issue 2, 2009, Pages 435~442
DOI : 10.5351/KJAS.2009.22.2.435
Multiple genes interacting is a difficult due to the limitations of parametric statistical method like as logistic regression for detection of gene effects that are dependent solely on interactions with other genes and with environmental exposures. Multifactor dimensionality reduction(MDR) statistical method by dummy variables was applied to identify interaction effects of single nucleotide polymorphisms(SNPs) responsible for longissimus mulcle dorsi area(LMA), carcass cold weight(CWT) and average daily gain(ADG) in a Hanwoo beef cattle population.