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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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The Korean Statistical Society
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Volume & Issues
Volume 16, Issue 6 - Nov 2009
Volume 16, Issue 5 - Sep 2009
Volume 16, Issue 4 - Jul 2009
Volume 16, Issue 3 - May 2009
Volume 16, Issue 2 - Mar 2009
Volume 16, Issue 1 - Jan 2009
Selecting the target year
VaR Estimation via Transformed GARCH Models
Park, Ju-Yeon ; Yeo, In-Kwon ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 891~901
DOI : 10.5351/CKSS.2009.16.6.891
In this paper, we investigate the approach to estimate VaR under the transformed GARCH model. The time series are transformed to approximate to the underlying distribution of error terms and then the parameters and the one-sided prediction interval are estimated with the transformed data. The back-transformation is applied to compute the VaR in the original data scale. The analyses on the asset returns of KOSPI and KOSDAQ are presented to verify the accuracy of the coverage probabilities of the proposed VaR.
A Modified RCA Index for Identifying Regional Strategic Industries
Kim, Hyun-Chul ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 903~913
DOI : 10.5351/CKSS.2009.16.6.903
In this paper, we suggested a modified revealed comparative advantage(RRCA) index for identifying regional strategic industries. The index is developed under the assumption that the concentration of industries in Korea is not based entirely on the comparative advantages. The Korean government has set up balanced development strategies since 2003 under the assumption too. The index is the ratio between the comparative advantage index and economic imbalance of the region. By the index, we selected strategic industries for 15 regions under the rule of 1) relative ratio of the index is more than 15%, 2) 1 to 3 regions for a industry according to the industry's output.
Identify Major Gene-Gene Interaction Effects Using SNPHarvester
Lee, Jea-Young ; Kim, Dong-Chul ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 915~923
DOI : 10.5351/CKSS.2009.16.6.915
The gene which is related in the disease of the human has been searched among numerous genes in GWA(Genome-Wide Association) research. However, most current statistical methods used to detect gene-gene interactions in disease association studies cannot be easily applied to handle the whole genome association study(GWAS) due to heavy computing. Therefore SNPHarvester is developed to find the main gene group among numerous genes. This research finds the superior gene groups which are related with the economic traits of the Korean beef cattle, not that of human, among sets of SNPs by using SNPHarvester, and also finds the superior genotypes which can enhance various qualities of Korean beef among SNP groups.
Imputation of Multiple Missing Values by Normal Mixture Model under Markov Random Field: Application to Imputation of Pixel Values of Color Image
Kim, Seung-Gu ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 925~936
DOI : 10.5351/CKSS.2009.16.6.925
There very many approaches to impute missing values in the iid. case. However, it is hardly found the imputation techniques in the Markov random field(MRF) case. In this paper, we show that the imputation under MRF is just to impute by fitting the normal mixture model(NMM) under several practical assumptions. Our multivariate normal mixture model based approaches under MRF is applied to impute the missing pixel values of 3-variate (R, G, B) color image, providing a technique to smooth the imputed values.
Link Importance Measures for Flow Network Systems
Lee, Seung-Min ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 937~943
DOI : 10.5351/CKSS.2009.16.6.937
A network with variable link capacities is considered to be in a functioning state if it can transmit a maximum flow which is greater than or equal to a specified amount of flow. The links are independent and either function or fail with known probability. No flow can be transmitted through a failed link. In this paper, we consider the measures of importance of a link in such networks. We define the structural importance and reliability importance, with respect to capacity, of a link when the required amount of flow is given. We also present the performance importance with respect to capacity. Numerical examples are presented as well for illustrative purpose.
Linear Trend Comparison of Repeated Measures Data among Treatments with a Control
Kwon, Jae-Hoon ; Kim, Dong-Jae ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 945~957
DOI : 10.5351/CKSS.2009.16.6.945
Repeated measurement data among several treatments with a control is often used in the field of medicine study. In this paper, we suggest a method for comparison of the linear trend of responds followed time among several treatments with a control based on repeated measurement data. First, we estimate slope from each subject and generate samples using the slope estimated previous. And then, we test the difference among treatment with a control by ANOVA F test, Jonckheere-Terpstra test, updated control group procedure using generated samples. Monte Carlo Simulation is adapted to compare the power and experimental significance levels in various configuration.
Dynamic Decision Tree for Data Mining
Choi, Byong-Su ; Cha, Woon-Ock ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 959~969
DOI : 10.5351/CKSS.2009.16.6.959
Decision tree is a typical tool for data classification. This tool is implemented in DAVIS (Huh and Song, 2002). All the visualization tools and statistical clustering tools implemented in DAVIS can communicate with the decision tree. This paper presents methods to apply data visualization techniques to the decision tree using a real data set.
Maximum Likelihood Estimation Using Laplace Approximation in Poisson GLMMs
Ha, Il-Do ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 971~978
DOI : 10.5351/CKSS.2009.16.6.971
Poisson generalized linear mixed models(GLMMs) have been widely used for the analysis of clustered or correlated count data. For the inference marginal likelihood, which is obtained by integrating out random effects is often used. It gives maximum likelihood(ML) estimator, but the integration is usually intractable. In this paper, we propose how to obtain the ML estimator via Laplace approximation based on hierarchical-likelihood (h-likelihood) approach under the Poisson GLMMs. In particular, the h-likelihood avoids the integration itself and gives a statistically efficient procedure for various random-effect models including GLMMs. The proposed method is illustrated using two practical examples and simulation studies.
Comparing the Use of Self and Peer Assessment: A Case Study in a Statistics Course
Han, Kyung-Soo ; Mun, Gil-Seong ; Ahn, Jeong-Yong ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 979~987
DOI : 10.5351/CKSS.2009.16.6.979
In this study, we compare the assessments made by self, peer and instructor in a statistics course. The goal is to investigate the following two questions: (1) Is it reasonable or fair to expect students to be responsible for assessing the work of their colleagues and themselves? (2) What are students' opinions about the learning effect after they participate in the assessment process? As part of the study investigating these questions, we designed a prototype for a Web-based assessment tool and a procedure to apply the assessment techniques in a statistics course. In addition, we collected and analyzed the data produced in the assessment processes from students and the instructor. The analysis results are summarized as follows: First, self assessment was not accord with instructor assessment, but peer assessment was similar to the assessment by instructor. This result reflected that it is reasonable or fair to expect students to be responsible for assessing the work of their colleagues. Second, peer assessment of their colleagues successfully helped students increase their understanding of the course, and the students increased their skills in the actual assessment process by assessing the work of their colleagues. Finally, many students indicated a high interest level on the assessments.
The Minimum Squared Distance Estimator and the Minimum Density Power Divergence Estimator
Pak, Ro-Jin ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 989~995
DOI : 10.5351/CKSS.2009.16.6.989
Basu et al. (1998) proposed the minimum divergence estimating method which is free from using the painful kernel density estimator. Their proposed class of density power divergences is indexed by a single parameter
which controls the trade-off between robustness and efficiency. In this article, (1) we introduce a new large class the minimum squared distance which includes from the minimum Hellinger distance to the minimum
distance. We also show that under certain conditions both the minimum density power divergence estimator(MDPDE) and the minimum squared distance estimator(MSDE) are asymptotically equivalent and (2) in finite samples the MDPDE performs better than the MSDE in general but there are some cases where the MSDE performs better than the MDPDE when estimating a location parameter or a proportion of mixed distributions.
An Algorithm for Support Vector Machines with a Reject Option Using Bundle Method
Choi, Ho-Sik ; Kim, Yong-Dai ; Han, Sang-Tae ; Kang, Hyun-Cheol ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 997~1004
DOI : 10.5351/CKSS.2009.16.6.997
A standard approach is to classify all of future observations. In some cases, however, it would be desirable to defer a decision in particular for observations which are hard to classify. That is, it would be better to take more advanced tests rather than to make a decision right away. This motivates a classifier with a reject option that reports a warning for those observations that are hard to classify. In this paper, we present the method which gives efficient computation with a reject option. Some numerical results show strong potential of the propose method.
The Unified Framework for AUC Maximizer
Jun, Jong-Jun ; Kim, Yong-Dai ; Han, Sang-Tae ; Kang, Hyun-Cheol ; Choi, Ho-Sik ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1005~1012
DOI : 10.5351/CKSS.2009.16.6.1005
The area under the curve(AUC) is commonly used as a measure of the receiver operating characteristic(ROC) curve which displays the performance of a set of binary classifiers for all feasible ratios of the costs associated with true positive rate(TPR) and false positive rate(FPR). In the bipartite ranking problem where one has to compare two different observations and decide which one is "better", the AUC measures the quantity that ranking score of a randomly chosen sample in one class is larger than that of a randomly chosen sample in the other class and hence, the function which maximizes an AUC of bipartite ranking problem is different to the function which maximizes (minimizes) accuracy (misclassification error rate) of binary classification problem. In this paper, we develop a way to construct the unified framework for AUC maximizer including support vector machines based on maximizing large margin and logistic regression based on estimating posterior probability. Moreover, we develop an efficient algorithm for the proposed unified framework. Numerical results show that the propose unified framework can treat various methodologies successfully.
Almost Sure Convergence for Asymptotically Almost Negatively Associated Random Variable Sequences
Baek, Jong-Il ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1013~1022
DOI : 10.5351/CKSS.2009.16.6.1013
We in this paper study the almost sure convergence for asymptotically almost negatively associated(AANA) random variable sequences and obtain some new results which extend and improve the result of Jamison et al. (1965) and Marcinkiewicz-Zygumnd strong law types in the form given by Baum and Katz (1965), three-series theorem.
Comparing More than Two Agreement Measures Using Marginal Association
Oh, Myong-Sik ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1023~1029
DOI : 10.5351/CKSS.2009.16.6.1023
Oh (2009) has proposed a likelihood ratio test for comparing two agreements for dependent observations based on the concept of marginal homogeneity and marginal stochastic ordering. In this paper we consider the comparison of more than two agreement measures. Simple ordering and simple tree ordering among agreement measures are investigated. Some test procedures, including likelihood ratio test, are discussed.
Determining the Optimal Subsampling Rate for Refusal Conversion in RDD Surveys
Park, In-Ho ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1031~1036
DOI : 10.5351/CKSS.2009.16.6.1031
Under recent dramatic declines in response rates, various procedures have been considered among survey practitioners to reduce nonresponse in order to avoid its potential impairment to the inference. In the random digit dialing telephone surveys, substantial efforts are often required to obtain the initial contact for the screener interview. To reduce a burden with higher data collection costs, refusal conversion can be administered only to a random portion of the sample, reducing nonresponse (bias) with an expense of sample variability increment due to the associated weight adjustment. In this paper, we provide ways to determine the optimal subsampling rate using a linear cost model. Our approach for refusal subsampling is to predetermine a random portion from the full sample and to apply refusal conversion efforts if needed only to the subsample.
Comparison of Methods for Detecting and Quantifying Variation in Copy Numbers of Duplicated Genes
Jeon, Jin-Tae ; Ahn, Sung-Jin ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1037~1046
DOI : 10.5351/CKSS.2009.16.6.1037
Copy number variations(CNVs) are known as one of the most important factors in susceptibility to genetic disorders because they affect expression levels of genes. In previous studies, pyrosequencing, mini-sequencing real-time polymerase chain reaction(PCR), invader assays and other techniques have been used to detect CNVs. However, the higher the copy number in a genome, the more difficult it is to resolve the copies, so a more accurate method for measuring CNVs and assigning genotype is needed. PCR followed by a quantitative oligonucleotide ligation assay(qOLA) was developed for quantifying CNVs. The aim of this study was to compare the two methods for detecting and quantifying the CNVs of duplicated gene: the published pyrosequencing assay(pyro_CNV) and the newly developed qOLA_CNV. The accuracy and precision of the assay were evaluated for porcine KIT, which was selected as a model locus. Overall, the root mean squares(RMSs) of bias and standard deviation of qOLA_CNV were 2.09 and 0.45, respectively. These values are less than half of those of pyro CNV.
Bandwidth Selection for Local Smoothing Jump Detector
Park, Dong-Ryeon ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1047~1054
DOI : 10.5351/CKSS.2009.16.6.1047
Local smoothing jump detection procedure is a popular method for detecting jump locations and the performance of the jump detector heavily depends on the choice of the bandwidth. However, little work has been done on this issue. In this paper, we propose the bootstrap bandwidth selection method which can be used for any kernel-based or local polynomial-based jump detector. The proposed bandwidth selection method is fully data-adaptive and its performance is evaluated through a simulation study and a real data example.
Estimation for the Half Logistic Distribution Based on Double Hybrid Censored Samples
Kang, Suk-Bok ; Cho, Young-Seuk ; Han, Jun-Tae ;
Communications for Statistical Applications and Methods, volume 16, issue 6, 2009, Pages 1055~1066
DOI : 10.5351/CKSS.2009.16.6.1055
Many articles have considered a hybrid censoring scheme, which is a mixture of Type-I and Type-II censoring schemes. We introduce a double hybrid censoring scheme and derive some approximate maximum likelihood estimators(AMLEs) of the scale parameter for the half logistic distribution under the proposed double hybrid censored samples. The scale parameter is estimated by approximate maximum likelihood estimation method using two different Taylor series expansion types. We also obtain the maximum likelihood estimator(MLE) and the least square estimator(LSE) of the scale parameter under the proposed double hybrid censored samples. We compare the proposed estimators in the sense of the mean squared error. The simulation procedure is repeated 10,000 times for the sample size n = 20(10)40 and various censored samples. The performances of the AMLEs and MLE are very similar in all aspects but the MLE and LSE have not a closed-form expression, some numerical method must be employed.