• 제목/요약/키워드: Statistical Modelling

검색결과 168건 처리시간 0.028초

Numerical and statistical analysis about displacements in reinforced concrete beams using damage mechanics

  • Pituba, Jose J. De C.;Delalibera, Rodrigo G.;Rodrigues, Fabio S.
    • Computers and Concrete
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    • 제10권3호
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    • pp.307-330
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    • 2012
  • This work intends to contribute for the improvement of the procedure suggested by Brazilian Technical Code that takes into account the cracked concrete stiffness in the estimative of the displacement of reinforced concrete beams submitted to service loads. A damage constitutive model accounting for induced anisotropy, plastic deformations and bimodular elastic response is used in order to simulate the concrete behaviour, while an elastoplastic behaviour is admitted for the reinforcement. The constitutive models were implemented in a program for bars structures analysis with layered finite elements. Initially, the damage model is briefly presented as well as the parametric identification of the materials that have been used in the reinforced concrete beams. After that, beams with different geometries and reinforcement area are analyzed and a statistical method (ANOVA) is employed in order to identify the main variables in the problem. Soon after, the same procedure is used with another resistance of concrete, where the compression strength is changed. The numerical responses are compared with the ones obtained by Brazilian Technical Code and experimental tests in order to validate the use of the damage model. Finally, some remarks are discussed based on responses presented in this work.

Forecasting interval for the INAR(p) process using sieve bootstrap

  • Kim, Hee-Young;Park, You-Sung
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.159-165
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    • 2005
  • Recently, as a result of the growing interest in modelling stationary processes with discrete marginal distributions, several models for integer valued time series have been proposed in the literature. One of theses models is the integer-valued autoregressive(INAR) models. However, when modelling with integer-valued autoregressive processes, there is not yet distributional properties of forecasts, since INAR process contain an accrued level of complexity in using the Steutal and Van Harn(1979) thinning operator 'o'. In this study, a manageable expression for the asymptotic mean square error of predicting more than one-step ahead from an estimated poisson INAR(1) model is derived. And, we present a bootstrap methods developed for the calculation of forecast interval limits of INAR(p) model. Extensive finite sample Monte Carlo experiments are carried out to compare the performance of the several bootstrap procedures.

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PROCESS ANALYSIS OF AUTOMOTIVE PARTS USING GRAPHICAL MODELLING

  • IRIKURA Norio;KUZUYA Kazuyoshi;NISHINA Ken
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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    • pp.295-300
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    • 1998
  • Recently graphical modelling is being studied as a useful process analysis tool for exploratory causal analysis. Graphical modelling is a presentation method that uses graphs to describe statistical models of the structures of multivariate data. This paper describes an application of this graphical modeling with two cases from the automotive parts industry. One case is the unbalance problem of the pulley, an automotive generator part. There is multivariate data of the product from each of the processes which are connected in the series. By means of exploratory causal analysis between the variables using graphical modeling, the key processes which causes the variation of the final characteristics and their mechanism of the causal relationship have become clear. Another case is, also, the unbalanced problem of automotive starter parts which consists of many parts and is manufactured by complex machinery and assembling process. By means of the similar technique, the key processes are obtained easily and the results are reasonable from technical knowledge.

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평균과 산포의 동시 모형화에 대한 모형검토 (Model Checking for Joint Modelling of Mean and Dispersion)

  • 하일도;이우동;조건호
    • Journal of the Korean Data and Information Science Society
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    • 제8권2호
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    • pp.195-209
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    • 1997
  • 일반화 선형모형의 범위를 크게 확장한 준-우도 모형에서 반응변수의 분산성분인 산포모수가 상수가아니라 어떤 공변량들의 값에 의존하여 변하는 경우, 평균과 산포의 동시 모형화가 요구된다. 본 논문에서는 준-우도 모형에서 평균과 산포의 동시 모형화를 통해 실제 자료를 쉽게 분석하도록 해주는 통계 패키지 GENSTAT(release 5.3.2, 1996)을 활용하여, Carrol과 Ruppert(1987,pp.46-47)에 의해 소개된 에스테르 분해효소 (esterase assay)의 자료에 대해 그래픽 방법을 이용한 모형검토를 통해서 기존의 평균모형 보다는 평균과 산포의 동시 모형화를 고려해야 하는 필요성을 언급한 뒤, 그 자료에 대한 적절한 평균과 산포의 동시 모형을 찾는 방법을 연구한다.

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Conditions For Hyper-EM And Large Graphical Modelling

  • 김성호;김성호
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2002년도 추계 학술발표회 논문집
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    • pp.293-298
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    • 2002
  • We propose an improved version of Kim (2000) to the effect that in principle we may deal with a graphical model of any size. Kim (2000) proposed a method of estimating parameters for a model of categorical variables which is too large to handle as a single model. We applied the proposed method to a simulated data of 158 binary variables.

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Modelling Count Responses with Overdispersion

  • Jeong, Kwang Mo
    • Communications for Statistical Applications and Methods
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    • 제19권6호
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    • pp.761-770
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    • 2012
  • We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

Szász-Kantorovich Type Operators Based on Charlier Polynomials

  • Kajla, Arun;Agrawal, Purshottam Narain
    • Kyungpook Mathematical Journal
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    • 제56권3호
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    • pp.877-897
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    • 2016
  • In the present article, we study some approximation properties of the Kantorovich type generalization of $Sz{\acute{a}}sz$ type operators involving Charlier polynomials introduced by S. Varma and F. Taşdelen (Math. Comput. Modelling, 56 (5-6) (2012) 108-112). First, we establish approximation in a Lipschitz type space, weighted approximation theorems and A-statistical convergence properties for these operators. Then, we obtain the rate of approximation of functions having derivatives of bounded variation.

One-step Least Squares Fitting of Variogram

  • Choi, Hye-Mi
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.539-544
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    • 2005
  • In this paper, we propose the one-step least squares method based on the squared differences to estimate the parameters of the variogram used for spatial data modelling, and discuss its asymptotic efficiency. The proposed method does not require to specify lags of interest and partition lags, so that we can delete the subjectiveness and ambiguity originated from the lag selection in estimating spatial dependence.

의사우도법을 이용한 공간 종속 모형의 추정 (Estimation of Spatial Dependence by Quasi-likelihood Method)

  • 이윤동;최혜미
    • 응용통계연구
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    • 제17권3호
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    • pp.519-533
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    • 2004
  • 본 연구에서는 베리오그램 추정을 통한 공간 종속성 추정방법에 있어서 의사우도 사용 방법을 설명하고, 모의실험을 통하여 전통적으로 사용되는 다른 방법들과 그 특성을 비교하고자 한다. 의사우도를 이용한 공간 종속 추정방법들은 그 통계적 성질이 우수할 뿐만 아니라, 전통적인 방법들에서 요구되어지는 관측치가 갖는 래그(lag)들을 미리 지정된 래그로 그룹화하는 과정이 필요 없어서 활용상의 우수성도 함께 가지고 있다. 또한, 이 방법에 대한 로버스트 방법을 개발하고 그 특성을 알아보고자 한다.

Experimental Designs for Computer Experiments and for Industrial Experiments with Model Unknown

  • Fang, Kai-Tai
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.277-299
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    • 2002
  • Most statistical designs, such as orthogonal designs and optimal designs, are based on a specific statistical model. It is very often that the experimenter does not completely know the underlying model between the response and the factors. In computer experiments, the underlying model is known, but too complicated. In this case we can treat the model as a black box, or model to be unknown. Both cases need a space filling design. The uniform design is one of space filling designs and seeks experimental points to be uniformly scattered on the domain. The uniform design can be used for computer experiments and also for industrial experiments when the underlying model is unknown. In this paper we shall introduce the theory and method of the uniform design and related data analysis and modelling methods. Applications of the uniform design to industry and other areas are discussed.