Bayesian Estimation and Prediction for Pareto Data
研究了基于经典帕累托分布数据，对不平等参数和精度参数进行贝叶斯推断，并预测未来观测值，比较了不同先验分布的效果。
Data from a classical Pareto distribution are to be used to make inferences about the inequality and precision parameters. In addition, it is desired to predict the behavior of further observations from the distribution. Three typical data configurations are considered (iid and two types of censoring). Dependent conjugate prior analyses are reviewed and are compared with an analysis involving independent priors for the inequality and precision parameters. It is argued that mathematical tractability should be, perhaps, a minor consideration in the choice of priors. A comparative example is included.