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Abtract
Bayesian statistics make inferences and doing estimation for unknown parameters with respect to posterior distributions. Under Bayes’ rule, functions for posterior distributions are established using likelihood function and prior distributions. However, these posterior functions usually have non-standard and unpredictable forms. So, generate a sample from posterior distribution is very crucial to make inferences in Bayesian statistics. The two algorithms for generating samples from a posterior distribution are proposed in this paper. We also apply both of the algorithms to generate samples for normal distribution and non-standard functions. The Shapiro-Wilk tests are performed to show the accuracy of the both algorithms.
Keyword: Generating random numbers, Bayesian statistics, standard posterior, non-standard posterior.
