• 제목/요약/키워드: prior distribution

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소프트웨어 신뢰도의 평가와 예측을 위한 베이지안 알고리즘 (Bayesian Algorithms for Evaluation and Prediction of Software Reliability)

  • 박만곤
    • 한국정보처리학회논문지
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    • 제1권1호
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    • pp.14-22
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    • 1994
  • 본 논문은 스미스의 베이지안 소프트웨어 신뢰도 성장모형을 기반으로 테스팅 단계에서의 소프트웨어 신뢰도에 대한 두가지 베이즈 추정량에 그에 대한 평가 알고 리즘을 제안하는데 목적이 있다. 그 방법으로 사전정보 클래스로서 일양사전분포보다 더 일반적인 베타사전분포 BE(a.b)를 사용하였다. 그 연구 과정으로 베이지안 추정절 차에 있어서 제곱오차결손함수와 해리스결손함수를 고려하고, 컴퓨터 시뮬레이션을 통 해서 소프트웨어 신뢰도에 대한 베이즈추정량들과 그에 따른 알고리즘을 이용하여 평 균자승오차 성능을 비교한다. 연구 결과로써 a가 크면 클수록 그리고 b가 적으면 적을 수록 해리스결손함수하의 소프트웨어 신뢰도의 베이즈추정량이 평균자승오차 성능의 관점에서는 더욱 유효하고, a 가 b보다 더 클 때 공액사전분포인 베타사전분포상의 소 프트웨어 신뢰도의 베이즈추정량이 비정보사전분포인 일양사전분포상에서 소프트웨어 신뢰도의 베이즈추정량보다는 성능이 더 좋다는 결론을 얻는다.

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Noninformative Priors for the Common Shape Parameter in the Gamma Distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제18권1호
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    • pp.247-257
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    • 2007
  • In this paper, we develop the noninformative priors for the common shape parameter in the gamma distributions. We develop the matching priors and reveal that the second order matching prior does not exist. It turns out that the one-at-a-time reference prior and the two group reference prior satisfy a first order probability matching criterion. Some simulation study is peformed.

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OBJECTIVE BAYESIAN APPROACH TO STEP STRESS ACCELERATED LIFE TESTS

  • Kim Dal-Ho;Lee Woo-Dong;Kang Sang-Gil
    • Journal of the Korean Statistical Society
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    • 제35권3호
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    • pp.225-238
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    • 2006
  • This paper considers noninformative priors for the scale parameter of exponential distribution when the data are collected in step stress accelerated life tests. We find the Jeffreys' and reference priors for this model and show that the reference prior satisfies first order matching criterion. Also, we show that there exists no second order matching prior in this problem. Some simulation results are given and we perform Bayesian analysis for proposed priors using some data.

Bayesian Estimation for the Reliability of Stress-Strength Systems Using Noninformative Priors

  • Kim, Byung-Hwee
    • International Journal of Reliability and Applications
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    • 제2권2호
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    • pp.117-130
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    • 2001
  • Consider the problem of estimating the system reliability using noninformative priors when both stress and strength follow generalized gamma distributions. We first treat the orthogonal reparametrization and then, using this reparametrization, derive Jeffreys'prior, reference prior, and matching priors. We next provide the suffcient condition for propriety of posterior distributions under those noninformative priors. Finally, we provide and compare estimated values of the system reliability based on the simulated values of the parameter of interest in some special cases.

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Noninformative Priors for the Stress-Strength Reliability in the Generalized Exponential Distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Communications for Statistical Applications and Methods
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    • 제18권4호
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    • pp.467-475
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    • 2011
  • This paper develops the noninformative priors for the stress-strength reliability from one parameter generalized exponential distributions. When this reliability is a parameter of interest, we develop the first, second order matching priors, reference priors in its order of importance in parameters and Jeffreys' prior. We reveal that these probability matching priors are not the alternative coverage probability matching prior or a highest posterior density matching prior, a cumulative distribution function matching prior. In addition, we reveal that the one-at-a-time reference prior and Jeffreys' prior are actually a second order matching prior. We show that the proposed reference prior matches the target coverage probabilities in a frequentist sense through a simulation study and a provided example.

Bayesian Inference for Multinomial Group Testing

  • Heo, Tae-Young;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • 제14권1호
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    • pp.81-92
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    • 2007
  • This paper consider trinomial group testing concerned with classification of N given units into one of k disjoint categories. In this paper, we propose Bayesian inference for estimating individual category proportions using the trinomial group testing model proposed by Bar-Lev et al. (2005). We compared a relative efficience (RE) based on the mean squared error (MSE) of MLE and Bayes estimators with various prior information. The impact of different prior specifications on the estimates is also investigated using selected prior distribution. The impact of different priors on the Bayes estimates is modest when the sample size and group size we large.

A Note on the Two Dependent Bernoulli Arms

  • 김달호;차영준;이재만
    • Journal of the Korean Data and Information Science Society
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    • 제13권2호
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    • pp.195-200
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    • 2002
  • We consider the Bernoulli two-armed bandit problem. It is well known that the my optic strategy is optimal when the prior distribution is concentrated at two points in the unit square. We investigate several cases in the unit square whether the my optic strategy is optimal or not. In general, the my optic strategy is not optimal when the prior distribution is not concentrated at two points in the unit square.

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Noninformative priors for linear function of parameters in the lognormal distribution

  • Lee, Woo Dong;Kim, Dal Ho;Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • 제27권4호
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    • pp.1091-1100
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    • 2016
  • This paper considers the noninformative priors for the linear function of parameters in the lognormal distribution. The lognormal distribution is applied in the various areas, such as occupational health research, environmental science, monetary units, etc. The linear function of parameters in the lognormal distribution includes the expectation, median and mode of the lognormal distribution. Thus we derive the probability matching priors and the reference priors for the linear function of parameters. Then we reveal that the derived reference priors do not satisfy a first order matching criterion. Under the general priors including the derived noninformative priors, we check the proper condition of the posterior distribution. Some numerical study under the developed priors is performed and real examples are illustrated.

Derivation of the Fisher Information Matrix for 4-Parameter Generalized Gamma Distribution Using Mathematica

  • Park, Tae Ryong
    • 통합자연과학논문집
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    • 제7권2호
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    • pp.138-144
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    • 2014
  • Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference where we calculate the posterior distribution using a noninformative prior distribution, and also in an example of metric functions in geometry. To estimate parameters in a distribution, we can use the Fisher information matrix. The more the number of parameters increases, the more its matrix form gets complicated. In this paper, by using Mathematica programs we derive the Fisher information matrix for 4-parameter generalized gamma distribution which is used in reliability theory.

베이즈 법칙의 활용을 위한 엑셀 매크로 (Excel macro for applying Bayes' rule)

  • 김재현;백호유
    • Journal of the Korean Data and Information Science Society
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    • 제22권6호
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    • pp.1183-1197
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    • 2011
  • 베이즈 법칙에서는 사전확률과 우도가 주어지고 어떤 실험결과가 일어났을 때 사후확률을 계산한다. 이러한 사후확률의 계산 문제를 엑셀 매크로를 이용하여 쉽게 계산할 수 있다. 또한 일련의 독립적이고 연속적인 실험결과에 따르는 사후확률도 편리하게 계산할 수 있다. 특히, 엑셀 매크로를 작성하면 작업창에서 반복된 계산의 입력과 출력이 쉽게 이루어진다. 본 논문에서는 베이즈 법칙의 활용을 위해서 엑셀 매크로를 작성하고 그것의 사용 예를 들었다.