• 제목/요약/키워드: Statistical Model

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집단 약동학 모형에 대한 통계학적 고찰 (A Statistical Approach to the Pharmacokinetic Model)

  • 이은경
    • 응용통계연구
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    • 제23권3호
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    • pp.511-520
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    • 2010
  • 약동학 모형은 약동학 모수들의 복잡한 비선형형태의 함수로 복잡한 미분방정식의 형태로 나타나기도 한다. 집단 약동학은 약동학 모형에서 약동학 모수들의 개인 간 차이를 나타내기 위해 이를 랜덤효과로 가정하므로 비선형 혼합 효과 모형이 된다. 본 논문에서는 임상약리학에서 약동학적 특징을 설명하기 위해 사용하는 집단 약동학 모형에 대한 통계학적 고찰을 해 본다. 또한 실제 임상자료를 이용하여 집단 약동학 모형을 적용하여 분석해 봄으로써 통계적 의미를 살펴본다.

A New Form of Nondestructive Strength-Estimating Statistical Models Accounting for Uncertainty of Model and Aging Effect of Concrete

  • Hong, Kee-Jeung;Kim, Jee-Sang
    • 비파괴검사학회지
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    • 제29권3호
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    • pp.230-234
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    • 2009
  • As concrete ages, the surrounding environment is expected to have growing influences on the concrete. As all the impacts of the environment cannot be considered in the strength-estimating model of a nondestructive concrete test, the increase in concrete age leads to growing uncertainty in the strength-estimating model. Therefore, the variation of the model error increases. It is necessary to include those impacts in the probability model of concrete strength attained from the nondestructive tests so as to build a more accurate reliability model for structural performance evaluation. This paper reviews and categorizes the existing strength-estimating statistical models of nondestructive concrete test, and suggests a new form of the strength-estimating statistical models to properly reflect the model uncertainty due to aging of the concrete. This new form of the statistical models will lay foundation for more accurate structural performance evaluation.

Statistical micro matching using a multinomial logistic regression model for categorical data

  • Kim, Kangmin;Park, Mingue
    • Communications for Statistical Applications and Methods
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    • 제26권5호
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    • pp.507-517
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    • 2019
  • Statistical matching is a method of combining multiple sources of data that are extracted or surveyed from the same population. It can be used in situation when variables of interest are not jointly observed. It is a low-cost way to expect high-effects in terms of being able to create synthetic data using existing sources. In this paper, we propose the several statistical micro matching methods using a multinomial logistic regression model when all variables of interest are categorical or categorized ones, which is common in sample survey. Under conditional independence assumption (CIA), a mixed statistical matching method, which is useful when auxiliary information is not available, is proposed. We also propose a statistical matching method with auxiliary information that reduces the bias of the conventional matching methods suggested under CIA. Through a simulation study, proposed micro matching methods and conventional ones are compared. Simulation study shows that suggested matching methods outperform the existing ones especially when CIA does not hold.

Statistical Process Control Procedure for Integral-Controlled Processes

  • Lee, Jaeheon;Park, Cangsoon
    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.435-446
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    • 2000
  • Statistical process control(SPC) and engineering process control(EPC) are two strategies for quality improvement that have been developed independently. EPC seeks to minimize variability by adjusting compensatory variables in order to make the process level close to the target, while SPC seeks to reduce variability by monitoring and eliminating causes of variation. One purpose of this paper is to propose the IMA(0,1,1) model as the in-control process model. For the out-of-control process model we consider two cases; one is the case with a step shift in the level, and the other is the case with a change in the nonstationarity. Another purpose is to suggest the use of an integrated process control procedure with adjustment and monitoring, which can consider the proposed process model effectively. An integrated control procedure will improve the process control activity significantly for cases of the proposed model, when compared to the procedure of using either EPC or SPC, since EPC will keep the process close to the target and SPC will eliminate special causes.

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GAUSS DISCREPANCY TYPE MEASURE OF DEGREE OF RESIDUALS FROM SYMMETRY FOR SQUARE CONTINGENCY TABLES

  • Tomizawa, Sadao;Murata, Mariko
    • Journal of the Korean Statistical Society
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    • 제21권1호
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    • pp.59-69
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    • 1992
  • A measure is proposed to represent the degree of residuals from the symmetry model for square contingency tables with nominal categories. The measure is derivedby modifying the sum of squared singular values for a skew symmetric matrix of the residuals from the symmetry model. The proposed measure would be useful for comparing the degree of residuals from the symmetry model in several tables.

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Statistical Correction of Numerical Model Forecasts for Typhoon Tracks

  • Sohn, Keon-Tae
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.295-304
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    • 2005
  • This paper concentrates on the prediction of typhoon tracks using the dynamic linear model (DLM) for the statistical correction of the numerical model guidance used in the JMA. The DLM with proposed forecast strategy is applied to reduce their systematic errors using the latest observation. All parameters of the DLM are updated dynamically and backward forecasting is performed to remove the effect of initial values.

STATISTICAL EVIDENCE METHODOLOGY FOR MODEL ACCEPTANCE BASED ON RECORD VALUES

  • Doostparast M.;Emadi M.
    • Journal of the Korean Statistical Society
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    • 제35권2호
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    • pp.167-177
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    • 2006
  • An important role of statistical analysis in science is interpreting observed data as evidence, that is 'what do the data say?'. Although standard statistical methods (hypothesis testing, estimation, confidence intervals) are routinely used for this purpose, the theory behind those methods contains no defined concept of evidence and no answer to the basic question 'when is it correct to say that a given body of data represent evidence supporting one statistical hypothesis against another?' (Royall, 1997). In this article, we use likelihood ratios to measure evidence provided by record values in favor of a hypothesis and against an alternative. This hypothesis is concerned on mean of an exponential model and prediction of future record values.

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.

A plastic strain based statistical damage model for brittle to ductile behaviour of rocks

  • Zhou, Changtai;Zhang, Kai;Wang, Haibo;Xu, Yongxiang
    • Geomechanics and Engineering
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    • 제21권4호
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    • pp.349-356
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    • 2020
  • Rock brittleness, which is closely related to the failure modes, plays a significant role in the design and construction of many rock engineering applications. However, the brittle-ductile failure transition is mostly ignored by the current statistical damage constitutive model, which may misestimate the failure strength and failure behaviours of intact rock. In this study, a new statistical damage model considering rock brittleness is proposed for brittle to ductile behaviour of rocks using brittleness index (BI). Firstly, the statistical constitutive damage model is reviewed and a new statistical damage model considering failure mode transition is developed by introducing rock brittleness parameter-BI. Then the corresponding damage distribution parameters, shape parameter m and scale parameter F0, are expressed in terms of BI. The shape parameter m has a positive relationship with BI while the scale parameter F0 depends on both BI and εe. Finally, the robustness and correctness of the proposed damage model is validated using a set of experimental data with various confining pressure.

A Doubly Winsorized Poisson Auto-model

  • Jaehyung Lee
    • Communications for Statistical Applications and Methods
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    • 제5권2호
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    • pp.559-570
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    • 1998
  • This paper introduces doubly Winsorized Poisson auto-model by truncating the support of a Poisson random variable both from above and below, and shows that this model has a same form of negpotential function as regular Poisson auto-model and one-way Winsorized Poisson auto-model. Strategies for maximum likelihood estimation of parameters are discussed. In addition to exact maximum likelihood estimation, Monte Carlo maximum likelihood estimation may be applied to this model.

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