• Title/Summary/Keyword: parametric estimation method

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A Comparison of Parametric and Non-parametric Approaches Dealing with Zero Responses in CVM Research (조건부 가치측정법에서 영(0)의 응답처리를 위한 모수적 추정법과 비모수적 추정법의 비교연구)

  • Lee, Joosuk;Choi, Eun-Chul
    • Environmental and Resource Economics Review
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    • v.22 no.2
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    • pp.281-307
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    • 2013
  • There has been some debates about zero willingness to pay in contingent valuation method research. Therefore, this paper tries to estimate and compare the results of various models to handle zero willingness to pay responses. For this purpose, we have employed parametric estimation such as the mixed model and the spike model, as well as non-parametric estimations. As a result, these models derived WTP estimate different from conventional model, but they also show some weakness. Therefore, in future research, more conservative estimate of the model should be to use rather than specific model.

Improvement in Long-term Behavior Estimation of Prestressed Composite Girders for Various Construction Sequences using Parametric Study (변수해석을 통한 프리스트레스트 합성거더의 시공단계별 장기거동 평가법 개선방안)

  • Bae, Doobyong;Oh, Chang Kook
    • Journal of Korean Society of Steel Construction
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    • v.25 no.4
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    • pp.369-377
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    • 2013
  • The age-adjusted effective modulus method has been known to provide more precise assessment than the traditional Yassumi method for long-term behavior estimation of prestressed composite girders. The age-adjusted effective modulus method, however, involves complicated calculation, thereby making the Yassumi method more prevalent in actual design. This study presents rational approaches to revise creep coefficients for the Yassumi method by using parametric study results obtained from the age-adjusted effective modulus method.

Wing weight estimation considering constraints of structural strength and stiffness in aircraft conceptual design

  • Bai, Chen;Mingqiang, Luo;Zhong, Shen;Zhe, Wu;Yiming, Man;Lei, Fang
    • International Journal of Aeronautical and Space Sciences
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    • v.15 no.4
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    • pp.383-395
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    • 2014
  • According to the requirement of wing weight estimation and frequent adjustments during aircraft conceptual design, a wing weight estimation method considering the constraints of structural strength and stiffness is proposed to help designers make wing weight estimations rapidly and accurately. This method implements weight predictions on the basis of structure weight optimization with stiffness constraints and strength constraints, which include achievement of wing shape parametric modeling, rapid structure layout, finite element (FE) model automated generation, load calculation, structure analysis, weight optimization, and weight computed based on modeling. A software tool is developed with this wing weight estimation method. This software can realize the whole process of wing weight estimation with the method and the workload of wing weight estimation is reduced because much of the work can be completed by the software. Finally, an example is given to illustrate that this weight estimation method is effective.

Fault Tolerant Control Design Using IMM Filter with an Application to a Flight Control System (IMM 필터를 이용한 고장허용 제어기법 및 비행 제어시스템에의 응용)

  • 김주호;황태현;최재원
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.87-87
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    • 2000
  • In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

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Sensitivity analysis of reliability estimation methods for attribute data to sample size and sampling points of time (계수형 데이터에 대한 신뢰도 추정방법의 샘플 수와 샘플링 시점 수에 따른 민감도 분석)

  • Son, Young-Kap;Ryu, Jang-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.2
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    • pp.581-587
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    • 2011
  • Reliability estimation methods using attribute data are widely used in reliability evaluation of various systems such as nuclear energy plants, food and drug, and space launch vehicles. This paper shows sensitivity analysis and comparison results of reliability estimation methods including a parametric estimation method in open literature with respect to both sample size and sampling points of time. And ways to improve accuracy of each reliability estimation method were proposed from the sensitivity analysis results.

A Novel Parametric Identification Method Using a Dynamic Encoding Algorithm for Searches (DEAS)

  • Kim, Jong-Wook;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.45.6-45
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    • 2002
  • In this paper, a novel optimization algorithm which searches for the local minima of a given cost function is proposed using the familiar property of a binary string, and is applied to the parametric identification of a continuous-time state equation by the estimation of system parameters as well as initial state values. A simple electrical circuit severs as an example, whose precise identification results show the superiority of the proposed algorithm.

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On Estimation of HPD Interval for the Generalized Variance Using a Weighted Monte Carlo Method

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.305-313
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    • 2002
  • Regarding to inference about a scalar measure of internal scatter of Ρ-variate normal population, this paper considers an interval estimation of the generalized variance, │$\Sigma$│. Due to complicate sampling distribution, fully parametric frequentist approach for the interval estimation is not available and thus Bayesian method is pursued to calculate the highest probability density (HPD) interval for the generalized variance. It is seen that the marginal posterior distribution of the generalized variance is intractable, and hence a weighted Monte Carlo method, a variant of Chen and Shao (1999) method, is developed to calculate the HPD interval of the generalized variance. Necessary theories involved in the method and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed method.

ML estimation using Poisson HGLM approach in semi-parametric frailty models

  • Ha, Il Do
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1389-1397
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    • 2016
  • Semi-parametric frailty model with nonparametric baseline hazards has been widely used for the analyses of clustered survival-time data. The frailty models can be fitted via an auxiliary Poisson hierarchical generalized linear model (HGLM). For the inferences of the frailty model marginal likelihood, which gives MLE, is often used. The marginal likelihood is usually obtained by integrating out random effects, but it often requires an intractable integration. In this paper, we propose to obtain the MLE via Laplace approximation using a Poisson HGLM approach for semi-parametric frailty model. The proposed HGLM approach uses hierarchical-likelihood (h-likelihood), which avoids integration itself. The proposed method is illustrated using a numerical study.

Dealing with the Willingness-to-Pay Data with Preference Intensity : A Semi-parametric Approach (선호강도를 반영한 지불의사액 자료의 준모수적 분석)

  • Yoo, Seung-Hoon
    • Environmental and Resource Economics Review
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    • v.14 no.2
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    • pp.447-474
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    • 2005
  • Respondents, in the willingness to pay (WTP) survey, may have preference intensity about their stated WTP values. This study elicited a post-decisional intensity measure for each observed WTP answer for gathering information on the degree of preference intensity. In order to deal with the WTP data with preference intensity, this paper considers using the Type 3 Tobit model. This is usually estimated by the parametric two-stage estimation method assuming homoskedastic and bivariate normal error structure. However, if the assumptions are not satisfied, the estimates are inconsistent. The author has tested the hypotheses of homoskedasticity and normality, and could not accept them at the 1% level. The assumptions required to estimate the parametric Type 3 model are, therefore, too strong to be satisfied. As an alternative the parametric model, this study applies a semiparametric Type 3 Tobit model. The results show that the semiparametric model significantly outperforms the parametric model, and that more importantly, the mean WTP from the parametric model is significantly different from that from the semiparametric model.

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A case study on calibration of computational model for a reasonable cost estimation of missile development program (A case of guidance & control system of X missile) (유도무기 연구개발사업의 합리적인 비용 추정을 위한 전산모델 보정방안 사례 연구 (X 유도무기 유도조종장치 사례를 중심으로))

  • Park, Chung-Hee
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.139-148
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    • 2014
  • In recent years, computational models using parametric estimation method have been developed and used widely for efficient cost analysis. In this research, by applying experienced data from Guidance and Control Systems in Missile System field, the cost analysis for engineering model and commercial computational model(Price H, HL, M, S) are conducted and its result is analysed, so that the difference between two models and its grounds are apprehended. Comparing the calibrated value of computational model based on the data base of similar equipment and the cost from the engineering estimation, the two results are very close. It means that the credibility of data is enhanced through calibration. Also, for cost analysis of similar components in the future, the method for calibration of the computational models is also examined. When estimating development cost in this research, although many parts have been estimated through uncertain elements, the reliability could have been enhanced by applying computational model which secures objectivity. It is a very reasonable estimation method by utilizing calibration of the computational models based on existing accumulated development data.