Some Remarks on the Use of Improper Priors for the Analysis of Exponential Regression Models
研究了指数回归模型中标准不当先验导致后验分布不当的问题，通过有限可加方法重新分析，指出观测数据并非无关，提醒谨慎使用不当先验。
We consider Bayesian inference on the exponential regression model. It is known that standard improper priors on the parameters of this model lead to marginal posterior distributions on one of the parameters involved which are also improper on the interval (0, 1). This has sometimes been interpreted as meaning that the observations are irrelevant. We re-analyse this problem using a finitely-additive approach and show that the above conclusion is not generally correct. This result emphasizes, once again, the dangers of routine approach to Bayesian inference using improper priors.