• Journal of Animal Science and Technology
• /
• 제48권3호
• /
• pp.337-344
• /
• 2006

본 연구는 Gibbs sampler와 MTDFREML 방법에 의해서 한우 도체형질의 유전력 및 유전(공)분산을 단형질 및 다형질 개체모형을 가지고 추정하고 비교 하였다. 배장근단면적(longissimus dorsi area), 등지방 두께(backfat thickness), 상강도(marbling score)의 유전 모수를 추정하였으며, 분석에 이용된 자료는 총 1,941두 이고, 혈연계수를 구하기 위한 혈통 자료는 23,058두를 이용하였다. 도체형질에 대한 유전력 추정 시 단형질과 다형질 개체모형에 의한 편차는 크게 나타나지 않았다. 단형질 개체모형에서 Gibbs sampler 방법을 이용한 추정에서는 LDA, BF 및 MS에서 각각 0.52, 0.59 및 0.42로서 고도의 유전력을 보였다. MTDFREML 방법을 통한 추정 시에는 LDA 0.41, BF 0.52로서 고도의 유전력을 보였으며, MS는 0.32로서 중도의 유전력을 보였다. 분석 방법에 의한 유전력 추정은 Gibbs sampler에 의한 방법이 MTDFREML에 의한 방법에 비해서 0.1정도 높게 추정되었다. MTDFREML 방법과 Gibbs Sampler 방법에 의한 도체 형질간의 유전상관은 LDA와 BF, MS 간에는 모두 부의 상관을 보였고, BF과 MS에서는 정의 상관을 보였다. MTDFREML과 Gibbs Sampler에서 이들의 분석 방법 간에 육종가 추정치에 대한 상관계수는 LDA와 BF에서는 0.989 이상의 높은 추정치를 보였으나, MS에 대해서는 이보다 다소 낮은 0.985를 나타내었다. 그리하여, 상강도(marbling score)와 같은 범주형 자료에 대한 유전분석은 기존의 선형의 정규분포를 가정한 REML방법에 의한 것 보다 범주형 모형을 설정하여 Gibbs sampling algorithm을 응용한 분석방법이 더 적합할 것으로 사료된다.

• Journal of applied mathematics & informatics
• /
• 제6권2호
• /
• pp.661-668
• /
• 1999

Reliability estimation using Gibbs sampler considered for modeling mixture exponential reliability problems. Gibbs sampler is developed to compute the features of the posterior distribution. Bayesian estimation of complicated functions requires simpler esti-mation techniques due to the mathematical difficulties involved in the Bayes approach. The Maximum likelihood estimator and the Gibbs estimator of reliability of the system are derived. By simula-tion risk behaviors of derived estimators are compared. model de-termination based on relative error is considered. A numerical study with a simulated data set is provided.

• 품질경영학회지
• /
• 제27권1호
• /
• pp.80-90
• /
• 1999

In this paper, reliability estimation using Gibbs sampler is considered for the mixture model with Gamma family, Gibbs sampler is derived to compute the features for the posterior distribution. By simulation study, the maximum likelihood estimator and the Gibbs estimator are obtained. A numerical study with a simulated data is provided.

• 응용통계연구
• /
• 제7권2호
• /
• pp.9-19
• /
• 1994

평가자간 평가 일치도(measure of agreement)를 나타내는 모수 $\kappa$와 양성 반응 비율 $\mu$를 지닌 베타-이항 분포 모형은 심리학 분야에서 많이 다루어지는 모형이다. 이 모형에서 $\kappa$에 대한 추정은 $\mu$가 0에 가까운 값을 가질 때 우도함수를 이용한 전통적 추론 방법의 적용이 어렵다. 본 논문에서는 이러한 문제를 Gibbs sampler를 이용한 Bayesian 분석 방법을 적용시켜 주변 사후 밀도 함수를 추정하였으며 이를 이용하여 Bayesian 추정값도 구하였다.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2014년도 하계학술대회
• /
• pp.77-78
• /
• 2014

A new MCMC method for optimization is presented in this paper, which is called the scanline block Gibbs sampler. Due to its slow convergence speed, traditional Markov chain Monte Carlo (MCMC) is not widely used. In contrast to the conventional MCMC method, it is more convenient to parallelize the scanline block Gibbs sampler. Since The main part of the scanline block Gibbs sampler is to calculate message between each edge, in order to accelerate the calculation of messages passing in scanline sampler, it is parallelized in GPU. It is proved that the implementation on GPU is faster than on CPU based on the experiments on the OpenGM2 benchmark.

• 대한수학회논문집
• /
• 제14권3호
• /
• pp.629-629
• /
• 1999

• Communications for Statistical Applications and Methods
• /
• 제10권1호
• /
• pp.203-210
• /
• 2003

In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

• 대한수학회논문집
• /
• 제14권3호
• /
• pp.627-633
• /
• 1999

Let the given distribution $\pi$ have a log-concave density which is proportional to exp(-V(x)) on $R^d$. We consider a Markov chain induced by the method Gibbs sampling having $\pi$ as its in-variant distribution and prove geometric ergodicity and the functional central limit theorem for the process.

• Journal of the Korean Data and Information Science Society
• /
• 제7권1호
• /
• pp.1-12
• /
• 1996

The Gibbs sampler is a substantially powerful tool in Bayesian analysis. However, it is necerssary to choose the numbert of iterations and the size of random samples. This problem has been studied by many researchers. The proposed procedures by them are generally difficult to apply to a practical problem. The attraction of the sampling based approaches is their conceptual simplicity and ease of implementation for users with available computing resources but without numerical analytic efforts. In this paper we consider the problem of determining the number of iterations t, which is simple to application.

• 한국통계학회:학술대회논문집
• /
• 한국통계학회 2004년도 학술발표논문집
• /
• pp.237-241
• /
• 2004

In standard time-to-event or survival analysis, the occurrence times of the event of interest are observed exactly or are right-censored. However in certain situations such as the AIDS data, the incubation period which is the time between HIV infection time and the diagnosis of AIDS is usually doubly censored. That is the HIV infection time Is interval censored and also the time of the diagnosis of AIDS is right censored. In this paper, we Impute the Interval censored infection time using the conditional mean imputation and estimate the coefficient factor of the regression analysis for the incubation period using Gibbs sampler. We applied parametric and semi-parametric methods for the analysis of the Incubation period and compared the results.