| Summary: | 碩士 === 中原大學 === 應用數學研究所 === 105 === OpenBUGS is so far the best statistical software for Bayesian analysis. Users only need to specify the model likelihood, the priors of parameters, the initial values and the data. Then, the OpenBUGS will apply Metropolis-Hastings algorithm to update parameters and estimate parameters by MCMC. However, the interface of OpenBUGS is not friendly. The operation procedure to run OpenBUGS is tedious. With the use of the R2OpenBUGS package, we can call OpenBUGS in R environment and perform other statistical procedures.
Logistic regression is a regression model for dichotomous dependent variable. The application of such model ranges from biology, business, and some other fields. In this paper, we propose to a random sample of logistic regression data using R, and then analyze by OpenBUGS via the R package R2OpenBUGS. Both R classical statistical analysis and Bayesian approach are performed using the real data and simulated data. And they agree to the similar results. Also, when the prior knowledge of parameters is clear, we see the Bayesian method yields to better estimation.
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