• 제목/요약/키워드: Two-parameter exponential model

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Bayesian Inference for the Two-Parameter Exponential Models : Type-II Censored Case

  • Sohn, Joong-Kweon;Kim, Heon-Joo
    • Journal of the Korean Statistical Society
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    • 제24권2호
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    • pp.313-335
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    • 1995
  • Suppose that we have $k(k \geq 2)$ populations (or systems), say $\pi_1, \cdots, \pi_k$, to be tested. Under the type-II censored testing without replacement we consider the problem of estimating the unknown parameters of interests and the reliability for a given time t for each population. Also we compare the perfomances of the proposed Bayes estimators with another estiamtors under the Jeffrey-type noninformative prior distribution.

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Reference priors for two parameter exponential stress-strength model

  • Kang, Sang-Gil;Kim, Dal-Ho;Le, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제21권5호
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    • pp.935-944
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    • 2010
  • In this paper, we develop the noninformative priors for the reliability in a stress-strength model where a strength X and a stress Y have independent exponential distributions with different scale parameters and a common location parameter. We derive the reference priors and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

위치모수를 가지는 이변량지수분포의 개발 (A bivariate extension of the two-parameter exponential distribution)

  • 홍연웅
    • 응용통계연구
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    • 제11권1호
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    • pp.185-192
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    • 1998
  • Freund(1961)가 제안한 이변량지수분포는 두 부품으로 이루어진 병렬체계의 상호종속적인 부품의 수명을 해석하는 등에 응용될 수 있어 널리 이용되고 있다. 본 연구에서는 위치모수를 가지는 이변량지수분포를 Freund 모형을 일반화시키는 차원에서 제안하고 모형의 통계적 성질 및 모수에 대한 최우추정량을 구하였다. 또한 최우추정량을 수정하여 편의는 감소시킬 수 있는 새로운 추정량을 제안하였다.

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How to Improve Classical Estimators via Linear Bayes Method?

  • Wang, Lichun
    • Communications for Statistical Applications and Methods
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    • 제22권6호
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    • pp.531-542
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    • 2015
  • In this survey, we use the normal linear model to demonstrate the use of the linear Bayes method. The superiorities of linear Bayes estimator (LBE) over the classical UMVUE and MLE are established in terms of the mean squared error matrix (MSEM) criterion. Compared with the usual Bayes estimator (obtained by the MCMC method) the proposed LBE is simple and easy to use with numerical results presented to illustrate its performance. We also examine the applications of linear Bayes method to some other distributions including two-parameter exponential family, uniform distribution and inverse Gaussian distribution, and finally make some remarks.

Reliability Estimation of a Two Mixture Exponential Model Using Gibbs sampler

  • Kim, Hee-Cheul;Kim, Pyong-Koo
    • 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.225-232
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    • 1998
  • A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. This data augmentation approach facilitates the specification of the transitional measure in the Markov Chain. Bayesian analysis of the mixture exponential model discusses using the Gibbs sampler. Parameter and reliability estimators are obtained. A numerical study is provided.

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Estimation of Smoothing Constant of Minimum Variance and its Application to Industrial Data

  • Takeyasu, Kazuhiro;Nagao, Kazuko
    • Industrial Engineering and Management Systems
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    • 제7권1호
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    • pp.44-50
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    • 2008
  • Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.

CONTINUOUS DATA ASSIMILATION FOR THE THREE-DIMENSIONAL SIMPLIFIED BARDINA MODEL UTILIZING MEASUREMENTS OF ONLY TWO COMPONENTS OF THE VELOCITY FIELD

  • Anh, Cung The;Bach, Bui Huy
    • 대한수학회지
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    • 제58권1호
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    • pp.1-28
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    • 2021
  • We study a continuous data assimilation algorithm for the three-dimensional simplified Bardina model utilizing measurements of only two components of the velocity field. Under suitable conditions on the relaxation (nudging) parameter and the spatial mesh resolution, we obtain an asymptotic in time estimate of the difference between the approximating solution and the unknown reference solution corresponding to the measurements, in an appropriate norm, which shows exponential convergence up to zero.

Computational procedures for exponential life model incorporating Bayes and shrinkage techniques

  • Al-Hemyari, Zuhair A.;Al-Dabag, H.A.;Al-Humairi, Ali Z.
    • International Journal of Reliability and Applications
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    • 제16권2호
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    • pp.55-79
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    • 2015
  • It is well known that using any additional information in the estimation of unknown parameters with new sample of observations diminishes the sampling units needed and minimizes the risk of new estimators. There are many rational reasons to assure that the existence of additional information in practice and there exists many practical cases in which additional information is available in the form of target value (initial value) about the unknown parameters. This article is described the problem of how the prior initial value about the unknown parameters can be utilized and combined with classical Bayes estimator to get a new combination of Bayes estimator and prior value to improve the properties of the new combination. In this article, two classes of Bayes-shrinkage and preliminary test Bayes-shrinkage estimators are proposed for the scale parameter of exponential distribution. The bias, risk and risk ratio expressions are derived and studied. The performance of the proposed classes of estimators is studied for different choices of constants engaged in the estimators. The comparisons, conclusions and recommendations are demonstrated.

하나의 확실한 이상점을 갖는 지수모형에서 모수에 대한 짹나이프 추정 (Jackknife parametric estimation in the two parameter exponential model with an identified outlier)

  • Jung Soo Woo;Chang Soo Lee
    • 응용통계연구
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    • 제7권2호
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    • pp.313-321
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    • 1994
  • 소표본에서 하나의 확실한 이상점을 갖는 지수모형에서 permanent 이론을 도입하여 표본들의 순서통계량의 분포를 정확한 형태로 유도하고, 이 결과를 이용하여 가정된 지수모형의 위치모수와 측도모수에 대한 최우추정량과 그 짹나이프 추정량을 편의와 평균제곱오차면에서 두 추정량의 소표본 성질을 비교하였다.

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Cavitation Compliance in 1D Part-load Vortex Models

  • Dorfler, Peter K
    • International Journal of Fluid Machinery and Systems
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    • 제10권3호
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    • pp.197-208
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    • 2017
  • When Francis turbines operate at partial load, residual swirl in the draft tube causes low-frequency pulsation of pressure and power output. Scale effects and system response may bias the prediction of prototype behavior based on laboratory tests, but could be overcome by means of a 1D analytical model. This paper deals with the two most important features of such a model, the compliance and the source of excitation. In a distributed-parameter version, compliance should be represented as an exponential function of local pressure. Lack of similarity due to different Froude number can thus be compensated. The normally unknown gas content in the vortex cavity has significant influence on the pulsation, and should therefore be measured and considered as a test parameter.