• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.683-692
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• 2010

This short article is concerned with a categorical time series obtained after clipping a heteroscedastic GARCH process. Estimation methods are discussed for the model parameters appearing both in the original process and in the resulting binary time series from a clipping (cf. Zhen and Basawa, 2009). Assuming AR-GARCH model for heteroscedastic time series, three data sets from Korean stock market are analyzed and illustrated with applications to calculating certain probabilities associated with the AR-GARCH process.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.271-290
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• 2017

We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

• IE interfaces
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• v.15 no.4
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• pp.409-425
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• 2002

This case study provides a market analysis methodology for overseas markets by applying statistical tools and the Six Sigma approach. The study suggests a procedure with seven steps to improve brands position in the market. These steps consist of interviewing consumers and floor salesmen of stores, surveying, analysis of correlation between brand position and customers satisfaction, analysis of relationship with companies and customer satisfaction factors, analysis of the customer satisfaction gap between companies, evaluating the importance of customer satisfaction factors, and suggestion for enhancement of brand position. The Six Sigma approach such as "Define", "Measure" and "Analyze" is used in this procedure, which is part of Six Sigma procedure, D-M-A-I-C (Define, Measure, Analyze, Improve, Control). Minitab and SAS are used for the statistical analysis.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.79-91
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• 2004

In this thesis, Bayesian parameter estimation procedure is discussed for the mean change model of multivariate normal random variates under the assumption of noninformative priors for all the parameters. Parameters are estimated by Gibbs sampling method. In Gibbs sampler, the change point parameter is generated by Metropolis-Hastings algorithm. We apply our methodology to numerical data to examine it.

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.25-36
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• 2006

Icosahedron and dodecahedron designs are experimental designs which can be used for response surface analysis for the case when three independent variables are involved. When we are interested in estimating the slope of a response surface, slope rot at ability is a desirable property. In this paper, we derive conditions for icosahedron and dodecahedron designs to have slope rotatability, and actually obtain some slope-rotatable icosahedron and dodecahedron designs. We also apply Park and Kim (1992)'s measure of slope rotatability to icosahedron and dodecahedron designs, and observe resultant facts.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.777-786
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• 2001

The autoregressive models have been used to describe a wade variety of time series. Then the problem of determining the order in the times series model is very important in data analysis. We consider the Bayesian approach for finding the order of autoregressive(AR) error models using the latent variable which is motivated by Tanner and Wong(1987). The latent variables are combined with the coefficient parameters and the sequential steps are proposed to set up the prior of the latent variables. Markov chain Monte Carlo method(Gibbs sampler and Metropolis-Hasting algorithm) is used in order to overcome the difficulties of Bayesian computations. Three examples including AR(3) error model are presented to illustrate our proposed methodology.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.297-319
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• 2016

Football match predictions are of great interest to fans and sports press. In the last few years it has been the focus of several studies. In this paper, we propose the Poisson regression model in order to football match outcomes. We applied the proposed methodology to two national competitions: the 2012-2013 English Premier League and the 2015 Brazilian Football League. The number of goals scored by each team in a match is assumed to follow Poisson distribution, whose average reflects the strength of the attack, defense and the home team advantage. Inferences about all unknown quantities involved are made using a Bayesian approach. We calculate the probabilities of win, draw and loss for each match using a simulation procedure. Besides, also using simulation, the probability of a team qualifying for continental tournaments, being crowned champion or relegated to the second division is obtained.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1442-1446
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• 2006

In this paper, the response surface modeling of the pretilt angle control in the nematic liquid crystal (NLC) on the homogeneous polyimide surface with different surface treatment is investigated The rubbing strength and the hard baking temperature are considered as input factors. After the design of experiments is performed, the process model is then explored using the response surface methodology. The analysis of variance is used to analyze the statistical significance and the effect plots are also investigated to examine the relationship between the process parameters and the response.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.125-137
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• 2012

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. For such reason, lots of intrusion detection system has been developed. Intrusion detection system has abilities to detect abnormal behavior and unknown intrusions also it can detect intrusions by using patterns studied from various penetration methods. Various algorithms are studying now such as the statistical method for detecting abnormal behavior, extracting abnormal behavior, and developing patterns that can be expected. Etc. This study using clustering of data mining and association rule analyzes detecting areas based on two models and helps design detection system which detecting abnormal behavior, unknown attack, misuse attack in a large network.

• Journal of The Korean Astronomical Society
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• v.21 no.2
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• pp.155-171
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• 1988

We have examined how sensitively the extinction value determined by the method of star-count depends on such factors as the plate limit, the size of counting reseau, the non-linearity in the number distribution of stars with magnitude, and the angular resolution demanded by the given problem. We let the Poisson distribution portray the statistical nature of the countings, and chose the region containing the globule Barnard 361 as an example field. Uncertainties due to various combinations of the factors are presented in graphic forms: (1) Dynamic range in the extinction measurements is evaluated as a function of reseau size for varying plate limits. (2) Statistical errors involved in the star-count are analized in terms of the signal-to-noise ratio, the plate limit and the reseau size. (3) Systematic error due to the non-linearity in the number distribution are thoroughly analized. (4) Finally, a methodology is presented for correcting the systematic error in the observed radial density gradient. These graphs are meant to be used in selecting proper size of the reseau and in estimating errors inherent to the star-count analysis.