• 제목/요약/키워드: probability procedure

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A Bayesian Variable Selection Method for Binary Response Probit Regression

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • 제28권2호
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    • pp.167-182
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    • 1999
  • This article is concerned with the selection of subsets of predictor variables to be included in building the binary response probit regression model. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the probit regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. The appropriate posterior probability of each subset of predictor variables is obtained through the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as the one with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

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A Bayesian Method for Narrowing the Scope of Variable Selection in Binary Response Logistic Regression

  • Kim, Hea-Jung;Lee, Ae-Kyung
    • 품질경영학회지
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    • 제26권1호
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    • pp.143-160
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    • 1998
  • This article is concerned with the selection of subsets of predictor variables to be included in bulding the binary response logistic regression model. It is based on a Bayesian aproach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the logistic regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. It is done by use of the fact that cdf of logistic distribution is a, pp.oximately equivalent to that of $t_{(8)}$/.634 distribution. The a, pp.opriate posterior probability of each subset of predictor variables is obtained by the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as that with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

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An Elimination Type Two-Stage Selection Procedure for Gamma Populations

  • Lee, Seung-Ho;Choi, Kook Lyeol
    • 품질경영학회지
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    • 제13권2호
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    • pp.29-36
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    • 1985
  • The problem of selecting the gamma population with the largest mean out of k gamma populations, each of which has the same shape parameter is considered. An elimination type two-stage procedure is proposed which guarantees the same probability requirement using the indifference-zone approach as does the single-stage procedure of Gibbons, Olkin and Sobel (1977). The two-stage procedure has the highly desirable property that the expected total number of observations required by the procedure is always less than that of the corresponding single-stage procedure regardless of the configuration of the population parameters.

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염해환경 콘크리트 구조물의 확률론적 내구성 해석 (A Probability-Based Durability Analysis of Concrete Structures in Chloride Containing Environments)

  • 권기준;김동백;정상화;채성태
    • 한국안전학회지
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    • 제22권3호
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    • pp.51-56
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    • 2007
  • In recent years, many research works have been carried out in order to obtain a more controlled durability and long-term performance of concrete structures in chloride containing environments. In particular, the development of new procedures for probability-based durability analysis/design has proved to be very valuable. Although there is still a lack of relevant data, this approach has been successfully applied to some new concrete structures. In this paper, the equation used for modelling of the chloride penetration was based on Fick's Second Law of Diffusion in combination with a time dependent diffusion coefficient. The probability analysis of the durability performance was performed by use of a Monte Carlo Simulation. The procedure was applied to an example based on limited data gathered in this country. The influences of each parameter on the durability of concrete structures are studied and some comments for durability design are given. The new procedure may be very useful in designing an important concrete structures in chloride containing environments. Also it may help to predict the service life of concrete structures under a given probability of failure.

지뢰지대 밀도별 접촉확률 산정 모델링 방안 (Modeling Scheme for Calculating Encounter Probability Versus Minefleld Density)

  • 백두현;이상헌
    • 한국국방경영분석학회지
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    • 제35권2호
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    • pp.77-86
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    • 2009
  • 접촉확률그래프는 한 대의 차량이 지뢰지대를 임의로 통과할 때 한 발의 지뢰가 폭발될 수 있는 확률을 측정한 그래프이다. 이 지뢰지대 밀도별 접촉확률 그래프는 한국 및 미(美) 육군의 야전교범에 제시되어 있으나 실 기동에 의한 데이터인지 워게임에 의한 결과치 인지 근거가 없는 실정이다. 본 논문에서는 신뢰할 만한 자료로서 근거가 없는 접촉확률 그래프를 컴퓨터 프로그램으로 절차식 모델을 구축하여 증명한다. 구축한 프로그램으로 산출된 결과치는 접촉확률그래프에 제시된 값과 거의 유사하게 나타낸다. 따라서 본 연구에서 제시한 절차식 모델은 모델링이 요구하는 타당성 및 모델자체의 검증에 있어 충분한 조건을 갖추었으며 다수 차량의 접촉확률을 계산하는데 있어서 매우 유용하다.

Low-discrepancy sampling for structural reliability sensitivity analysis

  • Cao, Zhenggang;Dai, Hongzhe;Wang, Wei
    • Structural Engineering and Mechanics
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    • 제38권1호
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    • pp.125-140
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    • 2011
  • This study presents an innovative method to estimate the reliability sensitivity based on the low-discrepancy sampling which is a new technique for structural reliability analysis. Two advantages are contributed to the method: one is that, by developing a general importance sampling procedure for reliability sensitivity analysis, the partial derivative of the failure probability with respect to the distribution parameter can be directly obtained with typically insignificant additional computations on the basis of structural reliability analysis; and the other is that, by combining various low-discrepancy sequences with the above importance sampling procedure, the proposed method is far more efficient than that based on the classical Monte Carlo method in estimating reliability sensitivity, especially for problems of small failure probability or problems that require a large number of costly finite element analyses. Examples involving both numerical and structural problems illustrate the application and effectiveness of the method developed, which indicate that the proposed method can provide accurate and computationally efficient estimates of reliability sensitivity.

계획기간의 연동적 고려 경우의 추계적 생산계획 (A Stochastic Production Planning Problem in Rolling Horizon Environment)

  • Sung, C. S.;Lee, Y. J.
    • 한국경영과학회지
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    • 제14권2호
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    • pp.67-74
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    • 1989
  • This paper considers single-product production and inventory management problem where cumulative demands up to each time period are mutually independent random variables(known) having continuous probability distributions and the associated cost-minimizing production schedule (when to produce and how much to produce) need be determined in rolling horizon environment. For the problem, both the production cost and the inventory holding and backlogging costs are included in the whole system cost. The probability distributions of these costs are expressed in terms of random demands, and utilized to exploit a solution procedure for a production schedule which minimizes the expected unit time system cost and also reduces the probability of rist that, for the first-period of each production cycle (rolling horizon), the cost of the "production" option will exceed that of the "non-production" one. Numerical examples are presented for the solution procedure illustration.cedure illustration.

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A SELECTION PROCEDURE FOR GOOD LOGISTICS POPULATIONS

  • Singh, Parminder;Gill, A.N.
    • Journal of the Korean Statistical Society
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    • 제32권3호
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    • pp.299-309
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    • 2003
  • Let ${\pi}_1,...,{\pi}_{k}$k($\geq$2) independent logistic populations such that the cumulative distribution function (cdf) of an observation from the population ${\pi}_{i}$ is $$F_{i}\;=\; {\frac{1}{1+exp{-\pi(x-{\mu}_{i})/(\sigma\sqrt{3})}}},\;$\mid$x$\mid$<\;{\infty}$$ where ${\mu}_{i}(-{\infty}\; < \; {\mu}_{i}\; <\; {\infty}$ is unknown location mean and ${\delta}^2$ is known variance, i = 1,..., $textsc{k}$. Let ${\mu}_{[k]}$ be the largest of all ${\mu}$'s and the population ${\pi}_{i}$ is defined to be 'good' if ${\mu}_{i}\;{\geq}\;{\mu}_{[k]}\;-\;{\delta}_1$, where ${\delta}_1\;>\;0$, i = 1,...,$textsc{k}$. A selection procedure based on sample median is proposed to select a subset of $textsc{k}$ logistic populations which includes all the good populations with probability at least $P^{*}$(a preassigned value). Simultaneous confidence intervals for the differences of location parameters, which can be derived with the help of proposed procedures, are discussed. If a population with location parameter ${\mu}_{i}\;<\;{\mu}_{[k]}\;-\;{\delta}_2({\delta}_2\;>{\delta}_1)$, i = 1,...,$textsc{k}$ is considered 'bad', a selection procedure is proposed so that the probability of either selecting a bad population or omitting a good population is at most 1­ $P^{*}$.

Determination of Probability of Component or Subsystem Failure

  • Lee, Seong-cheol
    • 품질경영학회지
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    • 제21권2호
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    • pp.121-130
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    • 1993
  • In this paper, we relate the reliability of the system to the reliabilities of the components or subsystems. We discussed the basic concept of system reliability and present a method to determine probabilities of failure of coherent system components under various conditions, especially forcused on probability of component or subsystem failure before system failure. Several examples illustrate the procedure.

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ATM스위치의 쎌 손실율 추정을 위한 Hybrid 시뮬레이션 기법 (A Hybrid Simulation Technique for Cell Loss Probability Estimation of ATM Switch)

  • 김지수;최우용;전치혁
    • 한국경영과학회지
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    • 제21권3호
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    • pp.47-61
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    • 1996
  • An ATM switch must deal with various kinds of input sources having different traffic characteristics and it must guarantee very small value of cel loss probability, about 10$^{8}$ -10$^{12}$ , to deal with loss-sensitive traffics. In order to estimate such a rate event probability with simulation procedure, a variance reduction technique is essential for obtaining an appropriate level of precision with reduced cost. In this paper, we propose a hybrid simulation technique to achieve reduction of variance of cell loss probability estimator, where hybrid means the combination of analytical method and simulation procedure. A discrete time queueing model with multiple input sources and a finite shared buffer is considered, where the arrival process at an input source and a finite shared buffer is considered, where the arrival process at an input source is governed by an Interrupted Bernoulli Process and the service rate is constant. We deal with heterogeneous input sources as well as homogeneous case. The performance of the proposed hybrid simulation estimator is compared with those of the raw simulation estimator and the importance sampling estimator in terms of variance reduction ratios.

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