• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.515-524
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• 2007

This paper deals with local linear estimation of fuzzy regression models based on Diamond(1998) as a new class of non-linear fuzzy regression. The purpose of this paper is to introduce a use of smoothing in testing for lack of fit of parametric fuzzy regression models.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.337-346
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• 2001

In this paper we consider the problem of identifying and testing the outliers in linear regression. first we consider the problem for testing the null hypothesis of no outliers. The test based on the ratio of two scale estimates is proposed. We show the asymptotic distribution of the test statistic by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure based on the suggested test is proposed and shown to perform fairly well. The forward sequential procedure is unaffected by masking and swamping effects because the test statistic is based on robust estimate.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.673-685
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• 2003

In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the problem for testing the null hypothesis of no outliers. A test based on the ratio of two residual scale estimates is proposed. We show the asymptotic distribution of the test statistics by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed and shown to perform fairly well. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.921-934
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• 2004

We consider the problem of identifying and testing outliers in linear regression. First, we consider the scale-ratio tests for testing the null hypothesis of no outliers. A test based on the ratio of two residual scale estimates is proposed. We show the asymptotic distribution of test statistics and investigate the properties of the test. Next we consider the problem of identifying the outliers. A forward procedure based on the suggested test is proposed and shown to perform fairly well. The forward procedure is unaffected by masking and swamping effects because the test statistics used a robust scale estimate.

• Structural Engineering and Mechanics
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• 제60권4호
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• pp.655-665
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• 2016

This paper aims to develop models to accurately predict the behavior of fresh concrete exposed to vibration using artificial neural networks (ANNs) model and regression model (RM). For this purpose, behavior of a full scale precast concrete mold was investigated experimentally and numerically. Experiment was performed under vibration with the use of a computer-based data acquisition system. Transducers were used to measure time-dependent lateral displacements at some points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using both ANNs and RM. For the modeling of ANNs: Experimental data were divided randomly into two parts. One of them was used for training of the ANNs and the remaining part was used for testing the ANNs. For the modeling of RM: Sinusoidal regression model equation was determined and the predicted data was compared with measured data. Finally, both models were compared with each other. The comparisons of both models show that the measured and testing results are compatible. Regression analysis is a traditional method that can be used for modeling with simple methods. However, this study also showed that ANN modeling can be used as an alternative method for behavior of fresh concrete exposed to vibration in precast concrete structures.

• 한국시스템다이내믹스연구
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• 제8권2호
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• pp.25-49
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• 2007

An important assumption of the classical linear regression model is that the disturbances appearing in the population regression function are homoskedastic; that is, they all have the same variance. If we persist in using the usual testing procedures despite heteroskedasticity, what ever conclusions we draw or inferences we make be very misleading. The contribution of this paper will be to the concrete procedure of the proper estimation when the heteroskedasticity does exist in the data, because the quality of dependent variable predictions, i.e., the estimated variance of the dependent variable, can be improved by giving consideration to the issues of regional homogeneity and/or heteroskedasticity across the research area. With respect to estimation, specific attention should be paid to the selection of the appropriate strategy in terms of the auxiliary regression model. The paper shows that by testing for heteroskedasticity, and by using robust methods in the presence of with and without heteroskedasticity, more efficient statistical inferences are provided.

• 지능정보연구
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• 제17권4호
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• pp.37-58
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• 2011

데이터베이스를 사용하는 프로그램을 테스트하는 것은 일반 소프트웨어의 경우보다 훨씬 더 복잡하고 어렵다. 테스트 데이터에 더하여 데이터베이스 상태가 테스트의 절차와 결과에 결정적인 영향을 미치는 것이 주요 원인이다. 테스트에 적합한 데이터베이스 상태를 만들어주려면 많은 시간과 노력이 필요한 것은 물론이거니와 IT와 업무에 대한 상당한 지식이 있어야 한다. 이러한 어려움에도 불구하고 데이터베이스 응용 프로그램의 테스트에 대한 연구와 지원은 매우 부족하다. 이 논문은 테스트에 알맞은 데이터베이스 상태의 생성과 유지에 관한 연구 결과를 보고한다. 연구의 핵심은 프로그램에서 사용하는 SQL을 로그파일에서 추출하여 분석한 결과와 데이터베이스 스키마와 테이블, 로그, 전문 등의 다양한 원천(source)에서 수집한 정보를 결합하여 프로그램의 테스트에 적합한 사전, 사후 상태를 자동으로 만들어주는 테스트 지원도구의 개발이다. 연구에서 제시한 절차와 도구는 단위 테스트와 통합 테스트의 지원과 더불어 회귀 테스트의 수행에 따르는 어려움을 극복하는데 큰 도움이 될 것이다. 실무적으로는 연구의 결과가 데이터베이스 상태의 생성과 유지에 소요되는 시간과 노력을 줄여 개발인력의 생산성을 제고하고, 다양한 케이스의 테스트와 회귀 테스트를 지원하여 대상 프로그램의 품질 향상에 기여할 것으로 기대한다. 학문적으로는 프로그램에서 사용하는 SQL의 패턴을 분석할 수 있는 상태 전이 도형과, 패턴의 표현 및 추론이 가능한 문법을 정의하여 전사적 응용 프로그램 테스트에 대한 폭 넓은 이해와 새로운 접근 방식을 가능하게 하였다.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.473-478
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• 2002

A test for a single outlier in multivariate regression with linear constraints on regression coefficients using a mean shift model is derived. It is shown that influential observations based on case-deletions in testing linear hypotheses are determined by two types of outliers that are mean shift outliers with or without linear constraints, An illustrative example is given.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제20권2호
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• pp.109-116
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• 2013

In this paper, we propose a Jonckheere type test statistic for testing the parallelism of k regression lines against ordered alternatives. The order restriction problems could arise in various settings such as location, scale, and regression problems. But most of theory about the statistical inferences under order restrictions has been developed to deal with location parameters. The proposed test is an application of Jonckheere's procedure to regression problem. Asymptotic normality and asymptotic distribution-free properties of the test statistic are obtained under some regularity conditions.

• 응용통계연구
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• 제24권6호
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• pp.1149-1160
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• 2011

기존의 frequentist 추론에 비해 Bayesian 추론에서의 가설 검정 및 모형 선택 문제는 학자들 간에 일치된 견해를 보이지 못하고 있으며 아직도 논란이 되는 것들이 많다. Bayesian 추론에서 가설 검정 및 모형 선택의 기준으로 널리 쓰이는 Bayes factor는 이해하기 쉬우나 여러 경우에 구하기 어려운 단점이 존재한다. 그 외에 다른 기준으로 Spiegelhalter 등 (2002)가 제시한 DIC(Deviance Information Criterion)과 frequentist 추론에서의 P-value에 대비되는 Bayesian P-value가 있다. 본 논문에서는 Swiss banknote 자료를 Bayesian 로지스틱 회귀모형으로 분석하고 관련 기준들을 구하여 각 기준들이 일관성 있는 결론을 보이는지 확인하고자 한다.