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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 17, Issue 6 - Nov 2010
Volume 17, Issue 5 - Sep 2010
Volume 17, Issue 4 - Jul 2010
Volume 17, Issue 3 - May 2010
Volume 17, Issue 2 - Mar 2010
Volume 17, Issue 1 - Jan 2010
Selecting the target year
An Application of Data-Mining Tool in Fraud Pension Payment Prediction
Cha, Kyung-Yup ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 1~8
DOI : 10.5351/CKSS.2010.17.1.001
This study tested the applicability of a Data mining tool in the analysis of massive National Pension data for the purpose of developing fraud pension payment prediction model. This study is identified significant variables for fraud pension payment through the statistical analysis process and developed prediction models using data mining methodology.
Calibration for Spatial Stratified Sampling Design
Byun, Jong-Seok ; Son, Chang-Kyoon ; Kim, Jong-Min ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 9~16
DOI : 10.5351/CKSS.2010.17.1.009
The sampling design for the spatial population studies needs a model assumption of a dependent relationship, where the interesting parameters can be the population mean, proportion and area. We know that the study of an interested spatial population, which is stratified by a geographical condition or shape, and the degree of distort of an estimation area is much useful. In light of this, if auxiliary information of the target variable such as wasted area contaminated by some material and the degree of distribution of animal or plants is available, then the spatial estimator might be improved through the calibration procedure. In this research, we propose the calibration procedure for the spatial stratified sampling in which we consider the one and two-dimensional auxiliary information.
Optimal k-Nearest Neighborhood Classifier Using Genetic Algorithm
Park, Chong-Sun ; Huh, Kyun ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 17~27
DOI : 10.5351/CKSS.2010.17.1.017
Feature selection and feature weighting are useful techniques for improving the classification accuracy of k-Nearest Neighbor (k-NN) classifier. The main propose of feature selection and feature weighting is to reduce the number of features, by eliminating irrelevant and redundant features, while simultaneously maintaining or enhancing classification accuracy. In this paper, a novel hybrid approach is proposed for simultaneous feature selection, feature weighting and choice of k in k-NN classifier based on Genetic Algorithm. The results have indicated that the proposed algorithm is quite comparable with and superior to existing classifiers with or without feature selection and feature weighting capability.
Coherent Forecasting in Binomial AR(p) Model
Kim, Hee-Young ; Park, You-Sung ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 27~37
DOI : 10.5351/CKSS.2010.17.1.027
This article concerns the forecasting in binomial AR(p) models which is proposed by Wei
(2009b) for time series of binomial counts. Our method extends to binomial AR(p) models a recent result by Jung and Tremayne (2006) for integer-valued autoregressive model of second order, INAR(2), with simple Poisson innovations. Forecasts are produced by conditional median which gives `coherent` forecasts, and we estimate the forecast distributions of future values of binomial AR(p) models by means of a Monte Carlo method allowing for parameter uncertainty. Model parameters are estimated by the method of moments and estimated standard errors are calculated by means of block of block bootstrap. The method is fitted to log data set used in Wei
Similarity of Sampling Sites by Water Quality
Kwon, Se-Hyug ; Lee, Yo-Sang ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 39~45
DOI : 10.5351/CKSS.2010.17.1.039
As the value of environment is increasing, the water quality has been a matter of interest to the nation and people. Research on water quality has been widely studied, but focused on geographical characteristic and river characteristics like inflow, outflow, quantity and speed of water. In this paper, two approaches to measure the similarity of sampling sites by using water quality data are discussed and compared with two-years empirical data of Yongdam-Dam. The existing method has calculated their similarities with principal component scores. The proposed approach in this paper use correlation matrix of water quality related variables and MDS for measuring the similarity, which is shown to be better in the sense of being clustering which is identical to geographical clustering since it can consider the time series pattern of water quality.
A Note on the Wick Integral with Respect to Fractional Brownian Sheet
Rhee, Joon-Hee ; Kim, Yoon-Tae ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 47~54
DOI : 10.5351/CKSS.2010.17.1.047
By using the white noise theory for fractional Brownian sheet, we give new representations of the Wick integrals of various types with respect to fractional Brownian sheet with Hurst parameters
Propensity Score Weighting Adjustment for Internet Surveys for Korean Presidential Election
Kim, Young-Won ; Be, Ye-Young ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 55~66
DOI : 10.5351/CKSS.2010.17.1.055
Propensity score adjustment(PSA) has been suggested as approach to adjustment for volunteer internet survey. PSA attempts to decrease the biases arising from noncoverage and nonprobability sampling in volunteer panel internet surveys. Although PSA is an appealing method, its application for internet survey regarding Korea presidential election and its effectiveness is not well investigated. In this study, we compare the Ni Korea internet survey with the telephone survey conducted by MBMR and KBS for 2007 Korean presidential election. The result of study show that the accuracy of internet survey can be improved by using PSA. And it is critical to include covariates that highly related to the voting tendency and the role of nondemographic variables seems important to improving PSA for Korea presidential election prediction.
Comparison of Step-Wise and Exact Maximum Likelihood Estimations on Cell Probabilities of Contingency Table
Lee, Sang-Eun ; Kang, Kee-Hoon ; Jeung, Seok-O ; Shin, Key-Il ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 67~77
DOI : 10.5351/CKSS.2010.17.1.067
In multinomial scheme with step-wise sampling, maximum likelihood estimates of multinomial probabilities are improved when some frequencies are merged. In this study, for cell probabilities in a I by J independent contingency tables, exact MLE and step-wise estimation methods are applied and the results are compared using MSE and Bias.
Note on the Equality of Variances in Two Sample t-Test
Kim, Sang-Cheol ; Lim, Jo-Han ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 79~88
DOI : 10.5351/CKSS.2010.17.1.079
Introductory statistic class proposes two tests for the equality of two population means according to the homogeneity of their variances. However, in practice, the variances are also unknown and practitioners often test their homogeneity before they do two sample t-test. This is also true in many popular statistical packages such as SAS and SPSS. In this paper, we study the type I error of this two stage procedure and propose a procedure to control it at a given significance level.
A Time Truncated Two-Stage Group Sampling Plan for Weibull Distribution
Aslam, Muhammad ; Jun, Chi-Hyuck ; Rasool, Mujahid ; Ahmad, Munir ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 89~98
DOI : 10.5351/CKSS.2010.17.1.089
In this paper, a two-stage group sampling plan based on the time truncated life test is proposed for the Weibull distribution. The design parameters such as the number of groups and the acceptance number in each stage are determined by satisfying the producer`s and consumer`s risks simultaneously when the group size and the test duration are specified. The acceptable reliability level is expressed by the ratio of the true mean life to the specified life. It was demonstrated from the comparison with single-stage group sampling plans that the proposed plan can reduce the average sample number or improve the operating characteristics.
Prediction Intervals for Proportional Hazard Rate Models Based on Progressively Type II Censored Samples
Asgharzadeh, A. ; Valiollahi, R. ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 99~106
DOI : 10.5351/CKSS.2010.17.1.099
In this paper, we present two methods for obtaining prediction intervals for the times to failure of units censored in multiple stages in a progressively censored sample from proportional hazard rate models. A numerical example and a Monte Carlo simulation study are presented to illustrate the prediction methods.
Statistical Considerations of the Add-On Test on Bioequivalence Trial
Park, Sang-Gue ; Nam, Bong-Hyun ; Chung, Yun-Ro ; Lee, Jae-Young ; Jeong, Gyu-Jin ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 107~115
DOI : 10.5351/CKSS.2010.17.1.107
The newly revised bioequivalence guideline of Korea allows the add-on test since July 1, 2008 and some discussion from statistical point of view would be needed for a practical use. The statistical model of add-on test is introduced and its two stage testing procedures are discussed. Meaningful statistical points of the add-on test are delivered through an illustrated example.
Analyzing Survival Data as Binary Outcomes with Logistic Regression
Lim, Jo-Han ; Lee, Kyeong-Eun ; Hahn, Kyu-S. ; Park, Kun-Woo ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 117~126
DOI : 10.5351/CKSS.2010.17.1.117
Clinical researchers often analyze survival data as binary outcomes using the logistic regression method. This paper examines the information loss resulting from analyzing survival time as binary outcomes. We first demonstrate that, under the proportional hazard assumption, this binary discretization does result in a significant information loss. Second, when fitting a logistic model to survival time data, researchers inadvertently use the maximal statistic. We implement a numerical study to examine the properties of the reference distribution for this statistic, finally, we show that the logistic regression method can still be a useful tool for analyzing survival data in particular when the proportional hazard assumption is questionable.
Group Sequential Tests Using both Type I and Type II Error Spending Rate Functions on Binomial Response
Kim, Dong-Uk ; Nam, Jin-Hyun ;
Communications for Statistical Applications and Methods, volume 17, issue 1, 2010, Pages 127~140
DOI : 10.5351/CKSS.2010.17.1.127
In interim analysis, group sequential tests are widely used for the ethical, scientific, and economic reasons. In this paper, we propose the group sequential tests using both type I and type II error spending rate functions when the response variable is discrete, especially binomial distribution, in the interim analysis. In addition, we propose new error spending rate function which covers the formerly proposed. Our method has good property that is flexible, fast and easily applicable. A numerical simulations are carried out to evaluate our method and it shows good performance.