• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.35-40
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• 2006

For the maritime traffic safety assessment of vessels navigating in harbor or fairway, simulation techniques by using shiphandling simulator system have been traditionally used. When designing the simulation experiments and when analyzing the simulation results, however, there has been a little systematic method. Ship-handling simulations can be regarded as a kind of statistical experiment by using ship-handling simulator system, which means that shiphandling simulation conditions should be designed statistically and that the simulation results should be statistically analyzed as well. For the safe and economic design of harbor and fairway, reasonable decisions based upon the scientific analysis of shiphandling simulation results are indispensable. In this paper, various statistical methods, such as Bayes theorem, statistical hypothesis testing, and probability distributions, are reviewed with a view to application to maritime traffic safety assessment. It is expected that more reasonable decisions on harbor and fairway design can be made from shiphandlers' view point by using statistical methods.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.46-51
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• 2007

In this paper, we propose a new data clustering method using local probability and hypothesis theory. To cluster the test data set we analyze the local area of the test data set using local probability distribution and decide the candidate class of the data set using mean standard deviation and variance etc. To decide each class of the test data, statistical hypothesis theory is applied to the decided candidate class of the test data set. For evaluating, the proposed classification method is compared to the conventional fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm. The simulation results show more accuracy than results of fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm.

• Journal of Distribution Science
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• v.12 no.8
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• pp.43-54
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• 2014

Purpose - This study was based on a theoretical consideration of the structural relationship between the support and control of the franchisor and the satisfaction and strategic response (voice, loyalty, exit, neglect) of the franchisee. First, based on the preceding research, this study systematically organized the type of support and control of the franchisor. Second, the study examined the effects of a franchisor's support and control on the expectancy disconfirmation between affiliated franchisees' expectations before a franchise agreement and performance after operating an affiliated store. Third, the study looked into the effects of expectancy disconfirmation relating to a franchisor's support and control on an affiliated franchisees' general satisfaction. Fourth, this study examined the influence of the general satisfaction of a franchisee on affiliated franchisees' response strategies. Research design, data, and methodology - In this study, the population comprised the nation's franchisors, and the sample comprised franchisees conducting business in Seoul and Gyeonggi-do. A self-administered questionnaire was used; the author and examiner explained the study's parameters to the interviewees in advance, to lessen the rate of rejection of the answers and to maintain reliability. The author distributed 350 copies of the questionnaire and collected 327 copies (93.4%). The author removed 54 copies of the sample, as these copies belonged to franchisees that were not registered by the Fair Trade Commission and/or were thought to have either defects or inadequate answers. The author selected an effective sample of 273 copies to enter data and to do the statistical analysis. Results - Both a reliability analysis and a confirmatory factor analysis were performed to measure reliability and validity, and a structural equation model was used to conduct the hypothesis test and investigate the models. The hypothesis was tested (Table 5). The models had a suitable fit, for instance, χ² = 447.663(df = 212, p = .000), χ²/df = 2.112, GFI = .881, AGFI = .858, RMR = .083, RMSEA = .067, NFI = .932, and CFI = .961. The hypothesis test results were as follows. Hypothesis 1 was accepted (C.R. = -2.339, p = .019). Hypothesis 2 was accepted (C.R. = 15.213, p = .000). Hypothesis 3 was accepted (C.R. = -2.631, p = .006). Hypothesis 4 was accepted (C.R. = 16.271, p = .000). Hypothesis 5 was accepted (C.R. = 2.391, p = .017). Hypothesis 6 was accepted (C.R. = 5.777, p = .000). Hypothesis 7 was accepted (C.R. = 17.153, p = .000). Hypothesis 8 was accepted (C.R. = 24.746, p = .000). Hypothesis 9 was accepted (C.R. = -10.150, p = .000). Hypothesis 10 was accepted (C.R. = -12.124, p = .000). Conclusions - The research results showed that expectations for a franchisor's support and control had a significant influence on expectation disconfirmation in a negative way, whereas the performance of support and control were found to have a significant influence on expectation disconfirmation in a positive way. In addition, the expectation disconfirmation of support and control was found to have a significant influence on satisfaction of franchisees in a positive way. Generally, regarding the research on control, control is found to have a negative influence on the satisfaction of franchisees, but this study proves that control is found to affect it in a positive way through conformity.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.415-431
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• 2002

A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

• Journal of Veterinary Clinics
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• v.26 no.3
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• pp.189-199
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• 2009

With the growing importance of evidence-based medicine, clinical or biomedical research relies critically on the validity and reliability of data, and the subsequent statistical inferences for medical decision-making may lead to valid conclusion. Despite widespread use of analytical techniques in papers published in the Journal of Veterinary Clinics statistical errors particularly in design of experiments, research methodology or data analysis methods are commonly encountered. These flaws often leading to misinterpretation of the data, thereby, subjected to inappropriate conclusions. This article is the first in a series of nontechnical introduction designed not to systemic review of medical statistics but intended to provide the journal readers with an understanding of common statistical concepts, including data scale, selection of appropriate statistical methods, descriptive statistics, data transformation, confidence interval, the principles of hypothesis testing, sampling distribution, and interpretation of results.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.67-72
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• 2002

A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.205-213
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• 2007

In this paper, the normal mixture model subjected to general linear restriction for component-means based on linear regression is proposed, and its fitting method by EM algorithm and Lagrange multiplier is provided. This model is applied to gene clustering of microarray expression data, which demonstrates it has very good performances for real data set. This model also allows to obtain the clusters that an analyst wants to find out in the fashion that the hypothesis for component-means is represented by the design matrices and the linear restriction matrices.

• Journal of the Korean Statistical Society
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• v.36 no.2
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• pp.257-274
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• 2007

This paper considers the tests for the presence of smooth transition non-linearity in the partially nonstationary vector autoregressive model. The transition parameters cannot be identified under the null hypothesis of linearity, and therefore this paper develops the tests for smooth transition nonlinearity, the associated asymptotic theory and the bootstrap inference. The Monte Carlo simulation evidence shows that the bootstrap inference generates moderate size and power performances.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.725-732
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• 2002

P-values are often perceived as measurements of degree of compatibility between the current data and the hypothesized model. In this paper, a new concept of Bayesian p-values is proposed and studied under the non-informative prior distributions, which can be thought as the Bayesian counterparts of the classical p-values in the sense of using the concept of significance level. The performances of the proposed Bayesian p-values are compared with those of the classical p-values through several examples.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.281-290
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• 2001

Symmetric estimation and recursive mean adjustment are considered to construct tests for the doble unit root hypothesis for both parametric and semiparametric time series models. It is shown that simultaneous application of symmetric estimation and recursive mean adjustment yields the most powerful test. Moreover, size property of the semiparametric test based on the simultaneous application is bet among all semiparametric tests.