周期单变点Poisson过程及参数Bayes估计

Poisson Process with Periodic Single Change Point and Bayesian Estimation of Parameter

根据某商场内累计逛街总人数,建立具有周期单变点的Poisson过程模型,研究周期等参数的满条件分布,并分别在绝对损失和平方损失作为损失函数的条件下,利用Gibbs与Metropolis-Hastings算法,讨论未知参数的Bayes估计.对给出的结果进行随机模拟与实例分析,表明两种损失函数下的Bayes估计均具有较好的精度.

According to the cumulative number of shopping people in a mall, we established the poisson process model with periodic single change point, and studied the full conditional distributions of period and other parameters. Under the conditions of absolute loss and squared loss as the loss function, we discussed the Bayesian estimation of unknown parameters by using Gibbs and Metropolis-Hastings algorithms. The results of random simulation and example analysis show that Bayesian estimations of two kinds of loss functions have good accuracy.