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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 18, Issue 6 - Nov 2011
Volume 18, Issue 5 - Sep 2011
Volume 18, Issue 4 - Jul 2011
Volume 18, Issue 3 - May 2011
Volume 18, Issue 2 - Mar 2011
Volume 18, Issue 1 - Jan 2011
Selecting the target year
Ratio-Cum-Product Estimators of Population Mean Using Known Population Parameters of Auxiliary Variates
Tailor, Rajesh ; Parmar, Rajesh ; Kim, Jong-Min ; Tailor, Ritesh ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 155~164
DOI : 10.5351/CKSS.2011.18.2.155
This paper suggests two ratio-cum-product estimators of finite population mean using known coefficient of variation and co-efficient of kurtosis of auxiliary characters. The bias and mean squared error of the proposed estimators with large sample approximation are derived. It has been shown that the estimators suggested by Upadhyaya and Singh (1999) are particular case of the suggested estimators. Almost ratio-cum product estimators of suggested estimators have also been obtained using Jackknife technique given by Quenouille (1956). An empirical study is also carried out to demonstrate the performance of the suggested estimators.
Support Vector Quantile Regression Using Asymmetric e-Insensitive Loss Function
Shim, Joo-Yong ; Seok, Kyung-Ha ; Hwang, Chang-Ha ; Cho, Dae-Hyeon ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 165~170
DOI : 10.5351/CKSS.2011.18.2.165
Support vector quantile regression(SVQR) is capable of providing a good description of the linear and nonlinear relationships among random variables. In this paper we propose a sparse SVQR to overcome a limitation of SVQR, nonsparsity. The asymmetric e-insensitive loss function is used to efficiently provide sparsity. The experimental results are presented to illustrate the performance of the proposed method by comparing it with nonsparse SVQR.
Outlier Detection Using Support Vector Machines
Seo, Han-Son ; Yoon, Min ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 171~177
DOI : 10.5351/CKSS.2011.18.2.171
In order to construct approximation functions for real data, it is necessary to remove the outliers from the measured raw data before constructing the model. Conventionally, visualization and maximum residual error have been used for outlier detection, but they often fail to detect outliers for nonlinear functions with multidimensional input. Although the standard support vector regression based outlier detection methods for nonlinear function with multidimensional input have achieved good performance, they have practical issues in computational cost and parameter adjustments. In this paper we propose a practical approach to outlier detection using support vector regression that reduces computational time and defines outlier threshold suitably. We apply this approach to real data examples for validity.
Maximum Tolerated Dose Estimate by Curve Fitting in Phase I Clinical Trial
Heo, Eun-Ha ; Kim, Dong-Jae ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 179~187
DOI : 10.5351/CKSS.2011.18.2.179
The purpose of a Phase I clinical trial is to estimate the maximum tolerated dose, MTD, of a new drug. In this paper, the MTD estimation method is suggested by curve fitting the dose-toxicity data to an S-shaped curve. The suggested MTD estimation method is compared with established MTD estimation procedures using a Monte Carlo simulation study.
Noninformative Priors for the Common Intraclass Correlation Coefficient
Kim, Dal-Ho ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 189~199
DOI : 10.5351/CKSS.2011.18.2.189
In this paper, we develop the noninformative priors for the common intraclass correlation coefficient when independent samples drawn from multivariate normal populations. We derive the first and second order matching priors. We reveal that the second order matching prior dose not match alternative coverage probabilities up to the second order and is not a HPD matching prior. It turns out that among all of the reference priors, one-at-a-time reference prior satisfies a second order matching criterion. Our simulation study indicates that one-at-a-time reference prior performs better than the other reference priors in terms of matching the target coverage probabilities in a frequentist sense.
A Note on the Efficiency Based Reliability Measures for Heterogeneous Populations
Cha, Ji-Hwan ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 201~211
DOI : 10.5351/CKSS.2011.18.2.201
In many cases, populations in the real world are composed of different subpopulations. Furthermore, in addition to the heterogeneity in the lifetimes of items, there also could be the heterogeneity in the efficiency or performance of items. In this case, the reliability measures should be defined in a different way. In this article, we consider the mixture of stochastically ordered subpopulations. Efficiency based reliability measures are defined when the performance of items in the subpopulations has different levels. Discrete and continuous mixing models are studied. The concept of the association between the lifetime and the performance of items in subpopulations is defined. It is shown that the consideration of efficiency can change the shape of the mixture failure rate dramatically especially when the lifetime and the performance of items in subpopulations are negatively associated. Furthermore, the modelling method proposed in this paper is applied to the case when the stress levels of the operating environment of items are different.
Local Centers of the Social Network
Huh, Myung-Hoe ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 213~217
DOI : 10.5351/CKSS.2011.18.2.213
For the social network of n nodes, one might be interested in finding k nodes to disseminate the information as quickly as possible or to identify key nodes of high "local centrality". I propose two algorithms for determining k "local centers" of the network and work on a real case.
Tests for Equality of Dispersions in the Generalized Bivariate Negative Binomial Regression Model with Heterogeneous Dispersions
Han, Sang-Moon ; Jung, Byoung-Cheol ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 219~227
DOI : 10.5351/CKSS.2011.18.2.219
In this paper, we proposed a generalized bivariate negative binomial distribution allowing heterogeneous dispersions on two dependent variables based on a trivariate reduction technique. In this model, we propose the score and LR tests for testing the equality of dispersions and compare the efficiencies of the proposed tests using a Monte Carlo study. The Monte Carlo study shows that the proposed score and LR tests prove to be an efficient test for the equality of dispersions in the view of the significance level and power. However, the score test is easier to compute than the LR test and it shows a slightly better performance than the LR test from the Monte Carlo study, we suggest the use of score tests for testing the equality of dispersions on two dependent variables. In addition, an empirical example is provided to illustrate the results.
Uniform Ergodicity and Exponential α-Mixing for Continuous Time Stochastic Volatility Model
Lee, O. ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 229~236
DOI : 10.5351/CKSS.2011.18.2.229
A continuous time stochastic volatility model for financial assets suggested by Barndorff-Nielsen and Shephard (2001) is considered, where the volatility process is modelled as an Ornstein-Uhlenbeck type process driven by a general L
vy process and the price process is then obtained by using an independent Brownian motion as the driving noise. The uniform ergodicity of the volatility process and exponential
-mixing properties of the log price processes of given continuous time stochastic volatility models are obtained.
A Comparison of Seasonal Linear Models and Seasonal ARIMA Models for Forecasting Intra-Day Call Arrivals
Kim, Myung-Suk ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 237~244
DOI : 10.5351/CKSS.2011.18.2.237
In call forecasting literature, both the seasonal autoregressive integrated moving average(ARIMA) type models and seasonal linear models have been popularly suggested as competing models. However, their parallel comparison for the forecasting accuracy was not strictly investigated before. This study evaluates the accuracy of both the seasonal linear models and the seasonal ARIMA-type models when predicting intra-day call arrival rates using both real and simulated data. The seasonal linear models outperform the seasonal ARIMA-type models in both one-day-ahead and one-week-ahead call forecasting in our empirical study.
Power Comparison between Methods of Empirical Process and a Kernel Density Estimator for the Test of Distribution Change
Na, Seong-Ryong ; Park, Hyeon-Ah ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 245~255
DOI : 10.5351/CKSS.2011.18.2.245
There are two nonparametric methods that use empirical distribution functions and probability density estimators for the test of the distribution change of data. In this paper we investigate the two methods precisely and summarize the results of previous research. We assume several probability models to make a simulation study of the change point analysis and to examine the finite sample behavior of the two methods. Empirical powers are compared to verify which is better for each model.
An Airline Scheduling Model and Solution Algorithms
AL-Sultan, Ahmed Thanyan ; Ishioka, Fumio ; Kurihara, Koji ;
Communications for Statistical Applications and Methods, volume 18, issue 2, 2011, Pages 257~266
DOI : 10.5351/CKSS.2011.18.2.257
The rapid development of airlines, has made airports busier and more complicated. The assignment of scheduled to available gates is a major issue for daily airline operations. We consider the over-constrained airport gate assignment problem(AGAP) where the number of flights exceeds the number of available gates, and where the objectives are to minimize the number of ungated flights and the total walking distance or connection times. The procedures used in this project are to create a mathematical model formulation to identify decision variables to identify, constraints and objective functions. In addition, we will consider in the AGAP the size of each gate in the terminal and also the towing process for the aircraft. We will use a greedy algorithm to solve the problem. The greedy algorithm minimizes ungated flights while providing initial feasible solutions that allow flexibility in seeking good solutions, especially in case when flight schedules are dense in time. Experiments conducts give good results.