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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 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
Empirical Bayes Estimation and Comparison of Credit Migration Matrices
Kim, Sung-Chul ; Park, Ji-Yeon ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 443~461
DOI : 10.5351/KJAS.2009.22.3.443
In order to overcome the lack of Korean credit rating migration data, we consider an empirical Bayes procedure to estimate credit rating migration matrices. We derive the posterior probabilities of Korean credit rating transitions by utilizing the Moody's rating migration data and the credit rating assignments from Korean rating agency as prior information and likelihood, respectively. Metrics based upon the average transition probability are developed to characterize the migration matrices and compare our Bayesian migration matrices with some given matrices. Time series data for the metrics show that our Bayesian matrices are stable, while the matrices based on Korean data have large variation in time. The bootstrap tests demonstrate that the results from the three estimation methods are significantly different and the Bayesian matrices are more affected by Korean data than the Moody's data. Finally, Monte Carlo simulations for computing the values of a portfolio and its credit VaRs are performed to compare these migration matrices.
Organizational Justice and Employee Behaviors: The Mediating Roles of Trust in CEO and Supervisor
Cho, Eun-Hyun ; Tak, Jin-Kook ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 463~477
DOI : 10.5351/KJAS.2009.22.3.463
This study was intended to examine the mediating roles of trust in CEO and supervisor on the relationships between organizational justice and employee behaviors. Data were collected from 4,055 employees across 18 different companies in Korea. Employees were asked to answer on a self-reported questionnaire. The two dimensions of organizational justice (i.e. procedural justice and distributive justice) were used. Employee behaviors were measured using counter-productive behavior and organizational citizenship behavior. Data were analyzed using a structural equation model. The hypothesized fully mediated model better fitted the data. Relative to distributive justice, procedural justice was more strongly related to both trust in CEO and trust in supervisor. But there were no significant differences in the degree of relationships between the two dimensions of trust and the two types of employee behaviors. These results showed that procedural justice is more important in enhancing trust in leader.
Adaptive Nearest Neighbors for Classification
Jhun, Myoung-Shic ; Choi, In-Kyung ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 479~488
DOI : 10.5351/KJAS.2009.22.3.479
-Nearest Neighbors Classification(KNNC) is a popular non-parametric classification method which assigns a fixed number
of neighbors to every observation without consideration of the local feature of the each observation. In this paper, we propose an Adaptive Nearest Neighbors Classification(ANNC) as an alternative to KNNC. The proposed ANNC method adapts the number of neighbors according to the local feature of the observation such as density of data. To verify characteristics of ANNC, we compare the number of misclassified observation with KNNC by Monte Carlo study and confirm the potential performance of ANNC method.
A Study on the Scoring Method for the Insurance Underwriting Using Generalized Linear Model
Lee, Chang-Soo ; Kwon, Hyuk-Sung ; Kim, Dong-Kwang ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 489~498
DOI : 10.5351/KJAS.2009.22.3.489
Underwriting is the first step for the administration of an insurance contract, which may result in stable profitability or unexpected loss for insurance company. Adequacy of underwriting criteria determines underwriting result. Generally, quantitative scoring system is used for underwriting. Method of evaluating risk for the scoring system is summing up scores for risk factors of a potential policyholder in consideration. Scores for each risk factor is predetermined. Current business environment for insurance companies makes underwriting profit more important, which means that insurance companies need more efficient underwriting method. This study suggests a reasonable approach to estimate risk relativities based on generalized linear model. Real data were used to quantify risk levels of groups of insureds for the design of underwriting model. Finally, effects in business volume and profitability of reflecting estimated underwriting scoring system are explained.
A Multi-Resolution Approach to Non-Stationary Financial Time Series Using the Hilbert-Huang Transform
Oh, Hee-Seok ; Suh, Jeong-Ho ; Kim, Dong-Hoh ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 499~513
DOI : 10.5351/KJAS.2009.22.3.499
An economic signal in the real world usually reflects complex phenomena. One may have difficulty both extracting and interpreting information embedded in such a signal. A natural way to reduce complexity is to decompose the original signal into several simple components, and then analyze each component. Spectral analysis (Priestley, 1981) provides a tool to analyze such signals under the assumption that the time series is stationary. However when the signal is subject to non-stationary and nonlinear characteristics such as amplitude and frequency modulation along time scale, spectral analysis is not suitable. Huang et al. (1998b, 1999) proposed a data-adaptive decomposition method called empirical mode decomposition and then applied Hilbert spectral analysis to decomposed signals called intrinsic mode function. Huang et al. (1998b, 1999) named this two step procedure the Hilbert-Huang transform(HHT). Because of its robustness in the presence of nonlinearity and non-stationarity, HHT has been used in various fields. In this paper, we discuss the applications of the HHT and demonstrate its promising potential for non-stationary financial time series data provided through a Korean stock price index.
A Statistical Approach to Examine the Impact of Various Meteorological Parameters on Pan Evaporation
Pandey, Swati ; Kumar, Manoj ; Chakraborty, Soubhik ; Mahanti, N.C. ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 515~530
DOI : 10.5351/KJAS.2009.22.3.515
Evaporation from surface water bodies is influenced by a number of meteorological parameters. The rate of evaporation is primarily controlled by incoming solar radiation, air and water temperature and wind speed and relative humidity. In the present study, influence of weekly meteorological variables such as air temperature, relative humidity, bright sunshine hours, wind speed, wind velocity, rainfall on rate of evaporation has been examined using 35 years(1971-2005) of meteorological data. Statistical analysis was carried out employing linear regression models. The developed regression models were tested for goodness of fit, multicollinearity along with normality test and constant variance test. These regression models were subsequently validated using the observed and predicted parameter estimates with the meteorological data of the year 2005. Further these models were checked with time order sequence of residual plots to identify the trend of the scatter plot and then new standardized regression models were developed using standardized equations. The highest significant positive correlation was observed between pan evaporation and maximum air temperature. Mean air temperature and wind velocity have highly significant influence on pan evaporation whereas minimum air temperature, relative humidity and wind direction have no such significant influence.
Principal Components Logistic Regression based on Robust Estimation
Kim, Bu-Yong ; Kahng, Myung-Wook ; Jang, Hea-Won ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 531~539
DOI : 10.5351/KJAS.2009.22.3.531
Logistic regression is widely used as a datamining technique for the customer relationship management. The maximum likelihood estimator has highly inflated variance when multicollinearity exists among the regressors, and it is not robust against outliers. Thus we propose the robust principal components logistic regression to deal with both multicollinearity and outlier problem. A procedure is suggested for the selection of principal components, which is based on the condition index. When a condition index is larger than the cutoff value obtained from the model constructed on the basis of the conjoint analysis, the corresponding principal component is removed from the logistic model. In addition, we employ an algorithm for the robust estimation, which strives to dampen the effect of outliers by applying the appropriate weights and factors to the leverage points and vertical outliers identified by the V-mask type criterion. The Monte Carlo simulation results indicate that the proposed procedure yields higher rate of correct classification than the existing method.
Stochastic Upper Bound for the Stationary Queue Lengths of GPS Servers
Kim, Sung-Gon ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 541~551
DOI : 10.5351/KJAS.2009.22.3.541
Generalized processor sharing(GPS) service policy is a scheduling algorithm to allocate the bandwidth of a queueing system with multi-class input traffic. In a queueing system with single-class traffic, the stationary queue length becomes larger stochastically when the bandwidth (i.e. the service rate) of the system decreases. For a given GPS server, we consider the similar problem to this. We define the monotonicity for the head of the line processor sharing(HLPS) servers in which the units in the heads of the queues are served simultaneously and the bandwidth allocated to each queue are determined by the numbers of units in the queues. GPS is a type of monotonic HLPS. We obtain the HLPS server whose queue length of a class stochastically bounds upper that of corresponding class in the given monotonic HLPS server for all classes. The queue lengths process of all classes in the obtained HLPS server has the stationary distribution of product form. When the given monotonic HLPS server is GPS server, we obtain the explicit form of the stationary queue lengths distribution of the bounding HLPS server. Numerical result shows how tight the stochastic bound is.
Numbers in the Internet Web and Benford's Law
Jang, Dae-Heung ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 553~568
DOI : 10.5351/KJAS.2009.22.3.553
Using the information about the frequency of occurrence of numbers in WWW, we can find properties of the array of numbers and validate whether this array satisfies the several laws(Power law, Zipf's law, Benford's law).
Edge Detection using Morphological Amoebas Noisy Images
Lee, Won-Yeol ; Kim, Se-Yun ; Kim, Young-Woo ; Lim, Jae-Young ; Lim, Dong-Hoon ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 569~584
DOI : 10.5351/KJAS.2009.22.3.569
Edge detection in images has been widely used in image processing system and computer vision. Morphological edge detection has used structuring elements with fixed shapes. This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with PFOM and ROC curves. The Experiments demonstrate that these novel operators outperform classical morphological operations with a fixed, space-invariant structuring elements for edge detection applications.
A Concordance Study of the Preprocessing Orders in Microarray Data
Kim, Sang-Cheol ; Lee, Jae-Hwi ; Kim, Byung-Soo ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 585~594
DOI : 10.5351/KJAS.2009.22.3.585
Researchers of microarray experiment transpose processed images of raw data to possible data of statistical analysis: it is preprocessing. Preprocessing of microarray has image filtering, imputation and normalization. There have been studied about several different methods of normalization and imputation, but there was not further study on the order of the procedures. We have no further study about which things put first on our procedure between normalization and imputation. This study is about the identification of differentially expressed genes(DEG) on the order of the preprocessing steps using two-dye cDNA microarray in colon cancer and gastric cancer. That is, we check for compare which combination of imputation and normalization steps can detect the DEG. We used imputation methods(K-nearly neighbor, Baysian principle comparison analysis) and normalization methods(global, within-print tip group, variance stabilization). Therefore, preprocessing steps have 12 methods. We identified concordance measure of DEG using the datasets to which the 12 different preprocessing orders were applied. When we applied preprocessing using variance stabilization of normalization method, there was a little variance in a sensitive way for detecting DEG.
Comparing Survival Functions with Doubly Interval-Censored Data: An Application to Diabetes Surveyed by Korean Cancer Prevention Study
Jee, Sun-Ha ; Nam, Chung-Mo ; Kim, Jin-Heum ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 595~606
DOI : 10.5351/KJAS.2009.22.3.595
Two tests were introduced for comparing several survival functions with doubly interval-censored data and illustrated with data surveyed by Korean Cancer Prevention Study (Jee et al., 2005). The test which extended Kim et al. (2006)'s test to the doubly interval-censored data has an advantage over Sun (2006)'s test in terms of saving computation time because the proposed test only depends on the size of risk set, and also the proposed test is applicable to continuous failure time data as well as discrete failure time data unlike Sun's test. Comparing male with female groups on the incubation time of diabetes was highly different and the survival of female group was longer than that of male one. Regardless of gender, the difference in survival functions of four age groups was highly significant with p-value of less than 0.001. This trend was more remarkable for female group than for male one. Simulation results showed that the significance level of both tests was well controlled and the proposed test was better than Sun's test in terms of power.
Comparing Imputation Methods for Doubly Censored Data
Yoo, Han-Na ; Lee, Jae-Won ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 607~616
DOI : 10.5351/KJAS.2009.22.3.607
In many epidemiological studies, the occurrence times of the event of interest are right-censored or interval censored. In certain situations such as the AIDS data, however, the incubation period which is the time between HIV infection and the diagnosis of AIDS is usually doubly censored. In this paper, we impute the interval censored HIV infection time using three imputation methods. Mid imputation, conditional mean imputation and approximate Bayesian bootstrap are implemented to obtain right censored data, and then Gibbs sampler is used to estimate the coefficient factor of the incubation period. By using Bayesian approach, flexible modeling and the use of prior information is available. We applied both parametric and semi-parametric methods for estimating the effect of the covariate and compared the imputation results incorporating prior information for the covariate effects.
A Report on the Inter-Gene Correlations in cDNA Microarray Data Sets
Kim, Byung-Soo ; Jang, Jee-Sun ; Kim, Sang-Cheol ; Lim, Jo-Han ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 617~626
DOI : 10.5351/KJAS.2009.22.3.617
A series of recent papers reported that the inter-gene correlations in Affymetrix microarray data sets were strong and long-ranged, and the assumption of independence or weak dependence among gene expression signals which was often employed without justification was in conflict with actual data. Qui et al. (2005) indicated that applying the nonparametric empirical Bayes method in which test statistics were pooled across genes for performing the statistical inference resulted in the large variance of the number of differentially expressed genes. Qui et al. (2005) attributed this effect to strong and long-ranged inter-gene correlations. Klebanov and Yakovlev (2007) demonstrated that the inter-gene correlations provided a rich source of information rather than being a nuisance in the statistical analysis and they developed, by transforming the original gene expression sequence, a sequence of independent random variables which they referred to as a
-sequence. We note in this report using two cDNA microarray data sets experimented in this country that the strong and long-ranged inter-gene correlations were still valid in cDNA microarray data and also the
-sequence of independence could be derived from the cDNA microarray data. This note suggests that the inter-gene correlations be considered in the future analysis of the cDNA microarray data sets.
Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
Cheon, Soo-Young ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 627~634
DOI : 10.5351/KJAS.2009.22.3.627
Recently, the general contour Monte Carlo has been proposed by Liang (2004) as a space annealing version(ACMC) for optimization problems. The algorithm can be applied successfully to determine the ground configurations for the prediction of protein folding. In this approach, we use the distances between the consecutive
atoms along the peptide chain and the mapping sequences between the 20-letter amino acids and a coarse-grained three-letter code. The algorithm was tested on the real proteins. The comparison showed that the algorithm made a significant improvement over the simulated annealing(SA) and the Metropolis Monte Carlo method in determining the ground configurations.
A Case Study on Statistic-Based Policy: Use of the Housing Purchase Price Indices
Park, Jin-Woo ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 635~651
DOI : 10.5351/KJAS.2009.22.3.635
Democratization and advancement of a society requires the Government's commitment to evidence-based policy. Though statistic is known as one of the best available evidence, there has been only a few case studies to tell real stories about using statistics for policy making. The object of this study is to suggest some real stories about using the Housing Purchase Price Survey for some property policies. By reviewing the origin and development of the survey, we evaluate the design and analysis strategies adopted in the survey. In addition, we describe how the Housing Purchase Price Indices have been used by the Government for some property policies.
A Note on the Population Policy of 1983
Park, War-Lan ; Jung, Ji-Won ; Park, Hui-Chang ; Lee, Suk-Hoon ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 653~665
DOI : 10.5351/KJAS.2009.22.3.653
All the policies and plans need to be carried out at the proper times in order that they would work properly for what they are made for. It is will known that statistics are one of the most useful tools in deciding the proper times for the policies. In this paper we show how to use statistics in evaluating the policies already carried with respect to the time when they were executed in dealing with the population policy we had in 1983 when the total fertility rate hit the population replacement level 2.1. Two methods have been tried to show that the policy carried in 1983 missed the proper changing time. The one is to make forecasting only with the data possible before 1982 and show how close they can be to the real situation of today. The other is to show what would happen if the policies aiming to suppress population growth had been changed or abandoned. Both results from two methods give some quantified information about the population policy of 1983. Especially the prediction tells that we could have forecasted the problem of low fertility of this century in 1983.
The Effect of Survey Refusal and Noncontact on Nonresponse Error: For Economically Active Population Survey
Kim, Seo-Young ; Kwon, Soon-Pil ;
Korean Journal of Applied Statistics, volume 22, issue 3, 2009, Pages 667~676
DOI : 10.5351/KJAS.2009.22.3.667
This study investigates the effect of survey refusal and noncontact on the nonresponse error in the household survey. For this purpose we analyzed the data of the interviewer's field work report. The survey data quality is affected by nonresponse rate and nonresponse error, and also nonresponse rate measures the reliability of the survey data. The household survey mainly contains two types of nonresponses of refusals and noncontacts. These refusals and noncontacts have different effect on the nonresponse error. This could be a venue for future research interested in decreasing the error due to noncontacts and refusals.