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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Communications for Statistical Applications and Methods
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Journal DOI :
The Korean Statistical Society
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Volume & Issues
Volume 13, Issue 3 - Dec 2006
Volume 13, Issue 2 - Aug 2006
Volume 13, Issue 1 - Apr 2006
Selecting the target year
A Refinement on DETECT for Polytomous Test Data
Kim, Hae-Rim ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 467~477
DOI : 10.5351/CKSS.2006.13.3.467
A multidimensionality detecting procedure DETECT, based on conditional covariances between items, is extended and refined to deal with polytomous item data as well as binary one. A large body of simulation study shows extraordinary performance of DETECT in both enumerating degrees of multidimensionality in a test and discovering dimensionally distinctive item clusters. Real data study also provides very meaningful results, making DETECT a strong dimensionality assessment tool for the test data analysis.
Francis Gallon in the History of Statistics
Jo, Jae-Keun ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 479~490
DOI : 10.5351/CKSS.2006.13.3.479
Francis Gallon (1822-1911) introduced the term 'regression' and 'correlation' in the study on human inheritance of the stature from parents to their children. In almost every statistics textbook, superficial attentions have been given to him just as the inventor of the term 'regression'. Rereading his books and papers, we investigated problems he had tried to solve and the methods he had used to solve the problems. In addition, we tried to find the motivation that had led Gallon to take attention to the variation rather than the central tendency of observational data that had fascinated his forerunner Adloph Quetelet.
Bayesian Change-point Model for ARCH
Nam, Seung-Min ; Kim, Ju-Won ; Cho, Sin-Sup ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 491~501
DOI : 10.5351/CKSS.2006.13.3.491
We consider a multiple change point model with autoregressive conditional heteroscedasticity (ARCH). The model assumes that all or the part of the parameters in the ARCH equation change over time. The occurrence of the change points is modelled as the discrete time Markov process with unknown transition probabilities. The model is estimated by Markov chain Monte Carlo methods based on the approach of Chib (1998). Simulation is performed using a variant of perfect sampling algorithm to achieve the accuracy and efficiency. We apply the proposed model to the simulated data for verifying the usefulness of the model.
Kernel Inference on the Inverse Weibull Distribution
Maswadah, M. ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 503~512
DOI : 10.5351/CKSS.2006.13.3.503
In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.
On the Conditional Dependence Structure of Multivariate Random Variables
Baek, Jong-Il ; Park, Sung-Tae ; Chung, Sung-Mo ; Lee, Gil-Hwan ; Heo, Gil-Pyo ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 513~524
DOI : 10.5351/CKSS.2006.13.3.513
In this paper, we introduce a new notions of conditionally weak dependence and we study their properties, preservation of the conditionally weak independent and positive and negative quadrant dependent(CWQD) property under mixtures, limits, closure under convex combinations, and their interrelationships. Furthermore, we extend multivariate stochastic dependence to stronger conditions of dependence.
Bootstrapping and DNA Marker Mining of ILSTS098 Microsatellite Locus in Hanwoo Chromosome 2
Lee, Jea-Young ; Kwon, Jae-Chul ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 525~535
DOI : 10.5351/CKSS.2006.13.3.525
We describe tests for detecting and locating quantitative traits loci (QTL) for traits in Hanwoo. Lod scores and a permutation test have been described. From results of a permutation test to detect QTL, we select major DNA markers of ILSTS098 microsatellite locus in Hanwoo chromosome 2 for further analysis. K-means clustering analysis applied to four traits and eight DNA markers in ILSTS098 resulted in three cluster groups. We conclude that the major DNA markers of BMS1167 microsatellite locus in Hanwoo chromosome 2 are markers 105bp, 113bp and 115bp. Finally, bootstrap testing method has been adapted to calculate confidence intervals and for finding major DNA Markers.
Test for the Exponential Distribution Based on Multiply Type-II Censored Samples
Kang, Suk-Bok ; Lee, Sang-Ki ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 537~550
DOI : 10.5351/CKSS.2006.13.3.537
In this paper, we develope three modified empirical distribution function type tests, the modified Cramer-von Mises test, the modified Anderson-Darling test, and the modified Kolmogorov-Smirnov test for the two-parameter exponential distribution with unknown parameters based on multiply Type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.
Bayesian Hypothesis Testing for Intraclass Correlation Coefficient
Lee, Seung-A ; Kim, Dal-Ho ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 551~566
DOI : 10.5351/CKSS.2006.13.3.551
In this paper, we consider a Bayesian model selection for the intraclass correlation coefficient in familiar data. In particular, we compare two nested models such as the independence and intraclass models using the reference prior. A criterion for testing is the Bayesian Reference Criterion by Bernardo (1999) and the Intrinsic Bayes Factor by Berger and Pericchi (1996). We provide numerical examples using simulation data sets for illustration.
Classification of Microarray Gene Expression Data by MultiBlock Dimension Reduction
Oh, Mi-Ra ; Kim, Seo-Young ; Kim, Kyung-Sook ; Baek, Jang-Sun ; Son, Young-Sook ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 567~576
DOI : 10.5351/CKSS.2006.13.3.567
In this paper, we applied the multiblock dimension reduction methods to the classification of tumor based on microarray gene expressions data. This procedure involves clustering selected genes, multiblock dimension reduction and classification using linear discrimination analysis and quadratic discrimination analysis.
An Improved Method for Evaluating Network-Reliability with Variable Link-Capacities
Lee, Chong-Hyung ; Lee, Seung-Min ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 577~585
DOI : 10.5351/CKSS.2006.13.3.577
This paper presents a method for reliability evaluation of a telecommunication network with variable link-capacities when the simple paths of the network are known. The LP-EM, suggested by Lee and Park (2001), identifies a composite path as a subnetwork and adds only a minimal set of links at each step which gives maximal increase on the maximum capacity flow of the subnetwork. Thereby the LP-EM reduces the possible occurrence of redundant composite paths significantly over other existing methods. Based on the LP-EM, our method further reduces the possible redundancy by identifying such simple paths that could give no increase of maximum capacity flow on the current subnetwork and excluding those simple paths from consideration in the process of constructing composite paths.
Fractional Integration in the Context of Periodicity: A Monte Carlo Experiment and an Empirical Study
Gil-Alana Luis A. ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 587~605
DOI : 10.5351/CKSS.2006.13.3.587
Recent results in applied statistics have shown that the presence of periodicities in time series may influence the estimation and testing of the fractional differencing parameter. In this article, we provide further evidence on the issue by using several procedures of fractional integration. The results show that in the presence of periodicities, the order of integration can be erroneously detected. An empirical application in the context of seasonal data is also carried out at the end of the article.
Test and Estimation for Normal Mean Change
Kim, Jae-Hee ; Ryu, Jong-Eun ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 607~619
DOI : 10.5351/CKSS.2006.13.3.607
We consider the problem of testing the existence of change in mean and estimating the change-point when the data are from the normal distribution. A change-point estimator using the likelihood ratio test statistic, Gombay and Horvath (1990) test statistic, and nonparametric change-point estimator using Carlstein (1988) empirical distribution are studied when there exists one change-point in the mean. A power study is done to compare the change test statistics. And a comparison study of change-point estimators for estimation capability is done via simulations with S-plus software.
Bayesian Multiple Change-point Estimation in Normal with EMC
Kim, Jae-Hee ; Cheon, Soo-Young ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 621~633
DOI : 10.5351/CKSS.2006.13.3.621
In this paper, we estimate multiple change-points when the data follow the normal distributions in the Bayesian way. Evolutionary Monte Carlo (EMC) algorithm is applied into general Bayesian model with variable-dimension parameters and shows its usefulness and efficiency as a promising tool especially for computational issues. The method is applied to the humidity data of Seoul and the final model is determined based on BIC.
Comparison of Haseman-Elston Linkage Tests with Age-of-Onset or Affection Trait
Jung, Kyoung-Hee ; Song, Hae-Hiang ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 635~649
DOI : 10.5351/CKSS.2006.13.3.635
In this paper, we perform a simulation study of genetic model-free age-of-onset methods in linkage tests which has been proposed by Zhu et al. (1997). They performe. Haseman-Elston regression on a set of bipolar pedigree data using each of three dependent variables: a binary trait indicating disease concordance or discordance, a binary trait adjusted for age-of-onset, and the residuals from a survival analysis. We compare the powers of the proposed test statistics for various situations. Simulations that we have carried out show that the gains in power are observed when the residuals from a survival analysis are used in linkage tests.
Extension of PM Model with Random Maintenance Quality
Jung, Ki-Mun ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 651~656
DOI : 10.5351/CKSS.2006.13.3.651
Wu and Clements-Croome (2005) investigate the optimization problem of PM policies for situations where the quality of PM is a random variable with a certain probability distribution. However, they assume that the cost of preventive maintenance is constant, not depending on the quality of PM. Thus, this paper considers a periodic PM model when PM cost depends on the quality of PM activity. The optimal PM policy are presented for the extended PM model and the numerical examples are presented for illustrative purpose.
Minimum Variance Unbiased Estimation for the Maximum Entropy of the Transformed Inverse Gaussian Random Variable by Y=X
Choi, Byung-Jin ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 657~667
DOI : 10.5351/CKSS.2006.13.3.657
The concept of entropy, introduced in communication theory by Shannon (1948) as a measure of uncertainty, is of prime interest in information-theoretic statistics. This paper considers the minimum variance unbiased estimation for the maximum entropy of the transformed inverse Gaussian random variable by
. The properties of the derived UMVU estimator is investigated.
Comparison of Small Area Estimations by Sample Sizes
Kim, Jung-O ; Shin, Key-Il ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 669~683
DOI : 10.5351/CKSS.2006.13.3.669
Model-based methods are generally used for small area estimation. Recently Shin and Lee (2003) suggested a method which used spatial correlations between areas for data set including some auxiliary variables. However in case of absence of auxiliary variables, Direct estimator is used. Even though direct estimator is unbiased, the large variance of the estimator restricts the use for small area estimation. In this paper, we suggest new estimators which take into account spatial correlation when auxiliary variables are not available. We compared Direct estimator and the newly suggested estimators using MSE, MAE and MB.
Bayesian Inference for Predicting the Default Rate Using the Power Prior
Kim, Seong-W. ; Son, Young-Sook ; Choi, Sang-A ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 685~699
DOI : 10.5351/CKSS.2006.13.3.685
Commercial banks and other related areas have developed internal models to better quantify their financial risks. Since an appropriate credit risk model plays a very important role in the risk management at financial institutions, it needs more accurate model which forecasts the credit losses, and statistical inference on that model is required. In this paper, we propose a new method for estimating a default rate. It is a Bayesian approach using the power prior which allows for incorporating of historical data to estimate the default rate. Inference on current data could be more reliable if there exist similar data based on previous studies. Ibrahim and Chen (2000) utilize these data to characterize the power prior. It allows for incorporating of historical data to estimate the parameters in the models. We demonstrate our methodologies with a real data set regarding SOHO data and also perform a simulation study.
Statistical Method for Implementing the Experimenter Effect in the Analysis of Gene Expression Data
Kim, In-Young ; Rha, Sun-Young ; Kim, Byung-Soo ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 701~718
DOI : 10.5351/CKSS.2006.13.3.701
In cancer microarray experiments, the experimenter or patient which is nested in each experimenter often shows quite heterogeneous error variability, which should be estimated for identifying a source of variation. Our study describes a Bayesian method which utilizes clinical information for identifying a set of DE genes for the class of subtypes as well as assesses and examines the experimenter effect and patient effect which is nested in each experimenter as a source of variation. We propose a Bayesian multilevel mixed effect model based on analysis of covariance (ANACOVA). The Bayesian multilevel mixed effect model is a combination of the multilevel mixed effect model and the Bayesian hierarchical model, which provides a flexible way of defining a suitable correlation structure among genes.
Cluster Analysis with Balancing Weight on Mixed-type Data
Chae, Seong-San ; Kim, Jong-Min ; Yang, Wan-Youn ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 719~732
DOI : 10.5351/CKSS.2006.13.3.719
A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The performance of clustering algorithms with balancing weight on different similarity measures is demonstrated. Our experiments show that clustering algorithms with application of proper weight give competitive recovery level when a set of data with mixed numeric and multiple binary attributes is clustered.
Hanwoo(Korean Cattle) Traceability Using DNA Markers
Yeo, Jung-Sou ; Rhee, Sung-Won ; Choi, Yu-Mi ; Kwon, Jae-Chul ; Lee, Jea-Young ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 733~743
DOI : 10.5351/CKSS.2006.13.3.733
To apply and evaluate the effectiveness of genetic markers on Hanwoo traceability systems, samples of 33 Hanwoo individuals from Korean elite sire families were used, and five microsatellite markers were selected finally, which were located on chromosomes different chromosomes with the end sequencing of 100 HW-YUBAC that were recorded in the NCBI by Yeungnam University. Ten major microsatellite markers were selected from alleles amplified, their frequencies, H(Heterozygosity) and PIC(Polymorphism information content) with Hardy-Weinberg equilibrium. Next, in order to evaluate the power of the markers selected on the individual animal identification, the match probability(MP) and the relatedness coefficient(R) were computed.
Comparison of Bootstrap Methods for LAD Estimator in AR(1) Model
Kang, Kee-Hoon ; Shin, Key-Il ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 745~754
DOI : 10.5351/CKSS.2006.13.3.745
It has been shown that LAD estimates are more efficient than LS estimates when the error distribution is double exponential in AR(1) model. In order to explore the performance of LAD estimates one can use bootstrap approaches. In this paper we consider the efficiencies of bootstrap methods when we apply LAD estimates with highly variable data. Monte Carlo simulation results are given for comparing generalized bootstrap, stationary bootstrap and threshold bootstrap methods.
Graphical Methods for Hierarchical Log-Linear Models
Hong, Chong-Sun ; Lee, Ui-Ki ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 755~764
DOI : 10.5351/CKSS.2006.13.3.755
Most graphical methods for categorical data can describe the structure of data and represent a measure of association among categorical variables. Among them the polyhedron plot represents sequential relationships among hierarchical log-linear models for a multidimensional contingency table. This kind of plot could be explored to describe the differences among sequential models. In this paper we suggest graphical methods, containing all the information, that reflect the relationship among all log-linear models in a certain hierarchical structure. We use the ideas of a correlation diagram.
Weighted LS-SVM Regression for Right Censored Data
Kim, Dae-Hak ; Jeong, Hyeong-Chul ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 765~776
DOI : 10.5351/CKSS.2006.13.3.765
In this paper we propose an estimation method on the regression model with randomly censored observations of the training data set. The weighted least squares support vector machine regression is applied for the regression function estimation by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed estimation method.
On the Geometric Equivalence of Asymmetric Factorial Designs
Park, Dong-Kwon ; Park, Eun-Hye ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 777~786
DOI : 10.5351/CKSS.2006.13.3.777
Two factorial designs with quantitative factors are called geometrically equivalent if the design matrix of one can be transformed into the design matrix of the other by row and column permutations, and reversal of symbol order in one or more columns. Clark and Dean (2001) gave a sufficient and necessary condition (which we call the 'gCD condition') for two symmetric factorial designs with quantitative factors to be geometrically equivalent. This condition is based on the absolute value of the Euclidean(or Hamming) distance between pairs of design points. In this paper we extend the gCD condition to asymmetric designs. In addition, a modified algorithm is applied for checking the equivalence of two designs.
Estimation in Group Testing when a Dilution Effect exists
Kwon, Se-Hyug ;
Communications for Statistical Applications and Methods, volume 13, issue 3, 2006, Pages 787~794
DOI : 10.5351/CKSS.2006.13.3.787
In group testing, the test unit consists of a group of individuals and each group is tested to classify units from a population as infected or non-infected or estimate the infection rate. If the test group is infected, one or more individuals in the group are presumed to be infected. It is assumed in group testing that classification of group as positive or negative is without error. But, the possibility of false negatives as a result of dilution effects happens often in practice, specially in many clinical researches. In this paper, dilution effect models in group testing are discussed and estimation methods of infection rate are proposed when a dilution effect exists.