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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Communications for Statistical Applications and Methods
Journal Basic Information
Journal DOI :
The Korean Statistical Society
Editor in Chief :
Volume & Issues
Volume 19, Issue 6 - Nov 2012
Volume 19, Issue 5 - Sep 2012
Volume 19, Issue 4 - Jul 2012
Volume 19, Issue 3 - May 2012
Volume 19, Issue 2 - Mar 2012
Volume 19, Issue 1 - Jan 2012
Selecting the target year
Uniform Ergodicity of an Exponential Continuous Time GARCH(p,q) Model
Lee, Oe-Sook ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 639~646
DOI : 10.5351/CKSS.2012.19.5.639
The exponential continuous time GARCH(p,q) model for financial assets suggested by Haug and Czado (2007) is considered, where the log volatility process is driven by a general L
vy process and the price process is then obtained by using the same L
vy process as driving noise. Uniform ergodicity and
-mixing property of the log volatility process is obtained by adopting an extended generator and drift condition.
On Convergence of Weighted Sums of LNQD Random
Kim, So-Youn ; Baek, Jong-Il ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 647~654
DOI : 10.5351/CKSS.2012.19.5.647
We discuss the strong convergence for weighted sums of linearly negative quadrant dependent(LNQD) random variables under suitable conditions and the central limit theorem for weighted sums of an LNQD case is also considered. In addition, we derive some corollaries in LNQD setting.
Multiclass Support Vector Machines with SCAD
Jung, Kang-Mo ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 655~662
DOI : 10.5351/CKSS.2012.19.5.655
Classification is an important research field in pattern recognition with high-dimensional predictors. The support vector machine(SVM) is a penalized feature selector and classifier. It is based on the hinge loss function, the non-convex penalty function, and the smoothly clipped absolute deviation(SCAD) suggested by Fan and Li (2001). We developed the algorithm for the multiclass SVM with the SCAD penalty function using the local quadratic approximation. For multiclass problems we compared the performance of the SVM with the
penalty functions and the developed method.
Ratio Cum Regression Estimator for Estimating a Population Mean with a Sub Sampling of Non Respondents
Kumar, Sunil ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 663~671
DOI : 10.5351/CKSS.2012.19.5.663
In the present study, a combined ratio cum regression estimator is proposed to estimate the population mean of the study variable in the presence of a non-response using an auxiliary variable under double sampling. The expressions of bias and mean squared error(MSE) based on the proposed estimator is derived under double (or two stage) sampling to the first degree of approximation. Some estimators are also derived from the proposed class by allocating the suitable values of constants used. A comparison of the proposed estimator with the usual unbiased estimator and other derived estimators is carried out. An empirical study is carried out to demonstrate the performance of the suggested estimator and of others; it is endow that the empirical results backing the theoretical study.
ECM Algorithm for Fitting of Mixtures of Multivariate Skew t-Distribution
Kim, Seung-Gu ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 673~683
DOI : 10.5351/CKSS.2012.19.5.673
Cabral et al. (2012) defined a mixture model of multivariate skew t-distributions(STMM), and proposed the use of an ECME algorithm (a variation of a standard EM algorithm) to fit the model. Their estimation by the ECME algorithm is closely related to the estimation of the degree of freedoms in the STMM. With the ECME, their purpose is to escape from the calculation of a conditional expectation that is not provided by a closed form; however, their estimates are quite unstable during the procedure of the ECME algorithm. In this paper, we provide a conditional expectation as a closed form so that it can be easily calculated; in addition, we propose to use the ECM algorithm in order to stably fit the STMM.
A Note on the Robustness of the X Chart to Non-Normality
Lee, Sung-Im ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 685~696
DOI : 10.5351/CKSS.2012.19.5.685
These days the interest of quality leads to the necessity of control charts for monitoring the process in various fields of practical applications. The
chart is one of the most widely used tools for quality control that also performs well under the normality of quality characteristics. However, quality characteristics tend to have nonnormal properties in real applications. Numerous recent studies have tried to find and explore the performance of
chart due to non-normality; however previous studies numerically examined the effects of non-normality and did not provide any theoretical justification. Moreover, numerical studies are restricted to specific type of distributions such as Burr or gamma distribution that are known to be flexible but can hardly replace other general distributions. In this paper, we approximate the false alarm rate(FAR) of the
chart using the Edgeworth expansion up to 1/n-order with the fourth cumulant. This allows us to examine the theoretical effects of nonnormality, as measured by the skewness and kurtosis, on
chart. In addition, we investigate the effect of skewness and kurtosis on
chart in numerical studies. We use a skewed-normal distribution with a skew parameter to comprehensively investigate the effect of skewness.
Estimation of the Exponential Distributions based on Multiply Progressive Type II Censored Sample
Lee, Kyeong-Jun ; Park, Chan-Keun ; Cho, Young-Seuk ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 697~704
DOI : 10.5351/CKSS.2012.19.5.697
The maximum likelihood(ML) estimation of the scale parameters of an exponential distribution based on progressive Type II censored samples is given. The sample is multiply censored (some middle observations being censored); however, the ML method does not admit explicit solutions. In this paper, we propose multiply progressive Type II censoring. This paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply progressive Type II censoring. The scale parameter is estimated by approximate ML methods that use two different Taylor series expansion types (
). We also obtain the maximum likelihood estimator(MLE) of the scale parameter under the proposed multiply progressive Type II censored samples. We compare the estimators in the sense of the mean square error(MSE). The simulation procedure is repeated 10,000 times for the sample size n = 20 and 40 and various censored schemes. The
is better than MLE and
in the sense of the MSE.
Bayesian Analysis for Heat Effects on Mortality
Jo, Young-In ; Lim, Youn-Hee ; Kim, Ho ; Lee, Jae-Yong ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 705~720
DOI : 10.5351/CKSS.2012.19.5.705
In this paper, we introduce a hierarchical Bayesian model to simultaneously estimate the thresholds of each 6 cities. It was noted in the literature there was a dramatic increases in the number of deaths if the mean temperature passes a certain value (that we call a threshold). We estimate the difference of mortality before and after the threshold. For the hierarchical Bayesian analysis, some proper prior distribution of parameters and hyper-parameters are assumed. By combining the Gibbs and Metropolis-Hastings algorithm, we constructed a Markov chain Monte Carlo algorithm and the posterior inference was based on the posterior sample. The analysis shows that the estimates of the threshold are located at
and the mortality around the threshold changes from -1% to 2~13%.
Nonparametric Method using Placement in an Analysis of a Covariance Model
Hwang, Dong-Min ; Kim, Dong-Jae ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 721~729
DOI : 10.5351/CKSS.2012.19.5.721
Various methods control the influence of a covariate on a response variable. These methods are analysis of covariance(ANCOVA), RANK ANCOVA, ANOVA of (covariate-adjusted) residuals, and Kruskal-Wallis tests on residuals. Covariate-adjusted residuals are obtained from the overall regression line fit to the entire data set that ignore the treatment levels or factors. It is demonstrated that the methods on covariate-adjusted residuals are only appropriate when the regression lines are parallel and covariate means are equal for all treatments. In this paper, we proposed the new nonparametric method on the ANCOVA model, as applying joint placement in a one-way layout on residuals as described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed procedure with those of the previous procedure.
Determinants for Korean Film Success: Reflection of Mass Culture Code and the Interaction Effect of Director and Actor
Kwak, Ki-Ho ; Kim, Bo-Won ; Jo, Hyeon ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 731~741
DOI : 10.5351/CKSS.2012.19.5.731
The Korean film industry has grown fast since the 2000s in terms of entering the 50% market share level, the emergence of 10million box-office movies and export performance improvement; however, the earning rate of production and investment part has decreased and recorded a minus value since 2005. This article aims to find key the determinants for the success of Korean movies from 2001~2006, a period of high growth and success of the Korean film industry through a multiple regression analysis. This paper introduces new determinants such as the interaction effect of the director and lead actor as well as mass culture codes. Finally, the authors suggest some proposals to make the Korean Film Industry more profitable.
Concept of the One-Sided Variance with Applications
Park, Hyo-Il ;
Communications for Statistical Applications and Methods, volume 19, issue 5, 2012, Pages 743~750
DOI : 10.5351/CKSS.2012.19.5.743
In this study, we propose definitions for the one-sided variance for asymmetric distribution. We consider to apply the one-sided variance to the construction to define modified
, which is a definition for the process capability index for the asymmetric process distribution. Then we consider to obtain the consistent estimation for the one-sided variance and to apply to the various industrial fields.