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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 15, Issue 6 - Nov 2008
Volume 15, Issue 5 - Sep 2008
Volume 15, Issue 4 - Jul 2008
Volume 15, Issue 3 - May 2008
Volume 15, Issue 2 - Mar 2008
Volume 15, Issue 1 - Jan 2008
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On Perturbed Symmetric Distributions Associated with the Truncated Bivariate Elliptical Models
Kim, Hea-Jung ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 483~496
DOI : 10.5351/CKSS.2008.15.4.483
This paper proposes a class of perturbed symmetric distributions associated with the bivariate elliptically symmetric(or simply bivariate elliptical) distributions. The class is obtained from the nontruncated marginals of the truncated bivariate elliptical distributions. This family of distributions strictly includes some univariate symmetric distributions, but with extra parameters to regulate the perturbation of the symmetry. The moment generating function of a random variable with the distribution is obtained and some properties of the distribution are also studied. These developments are followed by practical examples.
Blocking Method of 2
Factorial and Fractional Factorial Designs in Blocks of Size Two by Using Defining Contrast
Choi, Byoung-Chul ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 497~507
DOI : 10.5351/CKSS.2008.15.4.497
Confounding techniques have to be used repeatedly in the situations where it is necessary to perform only 2 runs under homogeneous conditions in
factorial and fractional factorial experiment. Combinations of confounded
factorial and fractional factorial designs enable the estimation of all main effects and all of or a part of 2 factor interaction effects. Defining contrast are used for our designs and treatment combinations of designs to be run are presented.
Influence Function on the Coefficient of Variation
Lee, Yun-Hee ; Kim, Hong-Gie ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 509~516
DOI : 10.5351/CKSS.2008.15.4.509
We derive the influence function on the coefficient of variation. Empirical influence function and Sample influence function are used to verify the validity of the derived influence function. To show the validity of the influence function, we carry out simulations with random samples from normal distribution
, respectively. The simulation result proves that the derived influence function is very accurate in estimating changes in the coefficient of variation when an observation is deleted.
Time Series Using Fuzzy Logic
Jung, Hye-Young ; Choi, Seung-Hoe ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 517~530
DOI : 10.5351/CKSS.2008.15.4.517
In this paper we introduce a time series model using the triangle fuzzy numbers in order to construct a statistical relation for the data which is a sequence of observations which are ordered in time. To estimate the proposed fuzzy model we split of a universal set includes all observation into closed intervals and determine a number and length of the closed interval by the frequency of events belong to the interval. Also we forecast the data by using a difference between observations when the fuzzified numbers equal at successive times. To investigate the efficiency of the proposed model we compare the ordinal and the fuzzy time series model using examples.
Locally Powerful Unit-Root Test
Choi, Bo-Seung ; Woo, Jin-Uk ; Park, You-Sung ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 531~542
DOI : 10.5351/CKSS.2008.15.4.531
The unit root test is the major tool for determining whether we use differencing or detrending to eliminate the trend from time series data. Dickey-Fuller test (Dickey and Fuller, 1979) has the low power of test when the sample size is small or the true coefficient of AR(1) process is almost unit root and the Bayesian unit root test has complicated testing procedure. We propose a new unit root testing procedure, which mixed Bayesian approach with the traditional testing procedure. Using simulation studies, our approach showed locally higher powers than Dickey-Fuller test when the sample size is small or the time series has almost unit root and simpler procedure than Bayesian unit root test procedure. Proposed testing procedure can be applied to the time series data that are not observed as process with unit root.
Empirical Choice of the Shape Parameter for Robust Support Vector Machines
Pak, Ro-Jin ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 543~549
DOI : 10.5351/CKSS.2008.15.4.543
Inspired by using a robust loss function in the support vector machine regression to control training error and the idea of robust template matching with M-estimator, Chen (2004) applies M-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for the support vector machines. We are specially interested in the shape of the Huber's M-estimator in this context and propose a way to find the shape parameter of the Huber's M-estimating function. For simplicity, only the two-class classification problem is considered.
Testing Structural Changes in Triangular Data
Lee, Sung-Im ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 551~562
DOI : 10.5351/CKSS.2008.15.4.551
The loss reserve is defined as a provision for an insurer's liability for claims or an insurer's estimate of the amount an individual claim will ultimately cost. For the estimation of the loss reserve, the data which make up the claims in general is represented as run-off triangle. The chain ladder method has known as the most representative one in the estimation of loss reserves based on such run-off triangular data. However, this fails to capture change point in trend. In order to test of structural changes of development factors, we will present the test statistics and procedures. A real data analysis will also be provided.
Option Pricing and Sensitivity Evaluation Methodology: Improvement of Speed and Accuracy
Choi, Young-Soo ; Oh, Se-Jin ; Lee, Won-Chang ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 563~585
DOI : 10.5351/CKSS.2008.15.4.563
This paper presents how to improve the efficiency and accuracy in the pricing and sensitivity evaluation for derivatives, since the need for the evaluation of complicated derivatives is increased. The Monte Carlo(MC) simulation using the quasi random number instead of pseudo random number can improve the elapsed time and accuracy for the valuation of European-type derivatives. However, the quasi MC simulation method has its limit for applying it in the multi-dimensional case such as American-type and path-dependent options due to the increased correlation between dimensions as the dimension of random numbers is increased. In order to complement this problem, we develop a modified method in which correlation values are controlled to be below a pre-specified value. Thus, this method is applicable for the pricing of either derivatives ill which underlying assets or risk factors are several or derivatives having path-dependent or early redemption property. Furthermore, we illustrate that it is important to take an appropriate grid interval for the use of finite difference method(FDM) by applying the FDM to one example of non-symmetrical butterfly spreads.
Parallel Coordinate Plots of Mixed-Type Data
Kwak, Il-Youp ; Huh, Myung-Hoe ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 587~595
DOI : 10.5351/CKSS.2008.15.4.587
Parallel coordinate plot of Inselberg (1985) is useful for visualizing dozens of variables, but so far the plot's applicability is limited to the variables of numerical type. The aim of this study is to extend the parallel coordinate plot so that it can accommodate both numerical and categorical variables. We combine Hayashi's (1950, 1952) quantification method of categorical variables and Hurley's (2004) endlink algorithm of ordering variables for the parallel coordinate plot. In line with our former study (Kwak and Huh, 2008), we develop Andrews' type modification of conventional straight-lines parallel coordinate plot to visualize the mixed-type data.
The Calibration for Stratified Randomized Response Estimators
Son, Chang-Kyoon ; Hong, Ki-Hak ; Lee, Gi-Sung ; Kim, Jong-Min ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 597~603
DOI : 10.5351/CKSS.2008.15.4.597
In this paper, we propose the calibration procedure for the valiance reduction of the stratified Warner's randomized response estimators, which suggested by Hong et al. (1994) and Kim and Warde (2004), using auxiliary information at the population level. It is shown that the proposed calibration estimators are more efficient than the ordinary Warner's estimators.
Comparison of Two Dependent Agreements Using Test of Marginal Homogeneity
Oh, Myong-Sik ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 605~614
DOI : 10.5351/CKSS.2008.15.4.605
Oh (2008) has proposed the one-sided likelihood ratio test of the equality of two agreement measures. However the use of this test may be limited since the computations of test statistic and critical value are not easy. We propose a test for comparing two dependent agreements using some well known tests for marginal homogeneity, for instance, Bhapkar test, Stuart-Maxwell test. Data obtained from 2008 world figure skating championship ladies single is analyzed for illustration purposes.
Validation Comparison of Credit Rating Models for Categorized Financial Data
Hong, Chong-Sun ; Lee, Chang-Hyuk ; Kim, Ji-Hun ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 615~631
DOI : 10.5351/CKSS.2008.15.4.615
Current credit evaluation models based on only financial data except non-financial data are used continuous data and produce credit scores for the ranking. In this work, some problems of the credit evaluation models based on transformed continuous financial data are discussed and we propose improved credit evaluation models based on categorized financial data. After analyzing and comparing goodness-of-fit tests of two models, the availability of the credit evaluation models for categorized financial data is explained.
Variable Selection in PLS Regression with Penalty Function
Park, Chong-Sun ; Moon, Guy-Jong ;
Communications for Statistical Applications and Methods, volume 15, issue 4, 2008, Pages 633~642
DOI : 10.5351/CKSS.2008.15.4.633
Variable selection algorithm for partial least square regression using penalty function is proposed. We use the fact that usual partial least square regression problem can be expressed as a maximization problem with appropriate constraints and we will add penalty function to this maximization problem. Then simulated annealing algorithm can be used in searching for optimal solutions of above maximization problem with penalty functions added. The HARD penalty function would be suggested as the best in several aspects. Illustrations with real and simulated examples are provided.