• Title, Summary, Keyword: 깁스 샘플링

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The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model (NHPP 소프트웨어 신뢰도 모형에 대한 모수 추정 비교)

  • Kim, Hee-Cheul;Lee, Sang-Sik;Song, Young-Jae
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1269-1276
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    • 2004
  • The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.

Bayesian quantile regression analysis of private education expenses for high scool students in Korea (일반계 고등학생 사교육비 지출에 대한 베이지안 분위회귀모형 분석)

  • Oh, Hyun Sook
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.6
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    • pp.1457-1469
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    • 2017
  • Private education expenses is one of the key issues in Korea and there have been many discussions about it. Academically, most of previous researches for private education expenses have used multiple regression linear model based on ordinary least squares (OLS) method. However, if the data do not satisfy the basic assumptions of the OLS method such as the normality and homoscedasticity, there is a problem with the reliability of estimations of parameters. In this case, quantile regression model is preferred to OLS model since it does not depend on the assumptions of nonnormality and heteroscedasticity for the data. In the present study, the data from a survey on private education expenses, conducted by Statistics Korea in 2015 has been analyzed for investigation of the impacting factors for private education expenses. Since the data do not satisfy the OLS assumptions, quantile regression model has been employed in Bayesian approach by using gibbs sampling method. The analysis results show that the gender of the student, parent's age, and the time and cost of participating after school are not significant. Household income is positively significant in proportion to the same size for all levels (quantiles) of private education expenses. Spending on private education in Seoul is higher than other regions and the regional difference grows as private education expenditure increases. Total time for private education and student's achievement have positive effect on the lower quantiles than the higher quantiles. Education level of father is positively significant for midium-high quantiles only, but education level of mother is for all but low quantiles. Participating after school is positively significant for the lower quantiles but EBS textbook cost is positively significant for the higher quantiles.

A Study on Bayesian Approach of Software Stochastic Reliability Superposition Model using General Order Statistics (일반 순서 통계량을 이용한 소프트웨어 신뢰확률 중첩모형에 관한 베이지안 접근에 관한 연구)

  • Lee, Byeong-Su;Kim, Hui-Cheol;Baek, Su-Gi;Jeong, Gwan-Hui;Yun, Ju-Yong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.8
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    • pp.2060-2071
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    • 1999
  • The complicate software failure system is defined to the superposition of the points of failure from several component point process. Because the likelihood function is difficulty in computing, we consider Gibbs sampler using iteration sampling based method. For each observed failure epoch, we applied to latent variables that indicates with component of the superposition mode. For model selection, we explored the posterior Bayesian criterion and the sum of relative errors for the comparison simple pattern with superposition model. A numerical example with NHPP simulated data set applies the thinning method proposed by Lewis and Shedler[25] is given, we consider Goel-Okumoto model and Weibull model with GOS, inference of parameter is studied. Using the posterior Bayesian criterion and the sum of relative errors, as we would expect, the superposition model is best on model under diffuse priors.

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The Bayesian Approach of Software Optimal Release Time Based on Log Poisson Execution Time Model (포아송 실행시간 모형에 의존한 소프트웨어 최적방출시기에 대한 베이지안 접근 방법에 대한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.7
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    • pp.1-8
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    • 2009
  • In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. The optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement is generally accepted. The Bayesian parametric inference of model using log Poisson execution time employ tool of Markov chain(Gibbs sampling and Metropolis algorithm). In a numerical example by T1 data was illustrated. make out estimating software optimal release time from the maximum likelihood estimation and Bayesian parametric estimation.

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The NHPP Bayesian Software Reliability Model Using Latent Variables (잠재변수를 이용한 NHPP 베이지안 소프트웨어 신뢰성 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.6 no.3
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    • pp.117-126
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    • 2006
  • Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

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