主  題: A Posterior-Based Wald-Type Statistic for Hypothesis Testing

內(nèi)容簡介: A new Wald-type statistic is proposed for hypothesis testing based on Bayesian posterior distributions. The new statistic can be explained as a posterior version of Wald test and have several nice properties. First, it is well-defined under improper pridistributions. Second, it avoids Jeffreys-Lindley's paradox. Third, under the null hypothesis it follows a ­ distribution asymptotically, offering a pivotal test asymptotically. Fourth, it only requires inverting the posterior covariance for the parameters of interest. Fifth and perhaps most importantly, when a random sample from the posterior distribution (such as an MCMC output) is available, the proposed statistic can be obtained as a by-product of posterior simulation. In addition, the numerical standard error of the estimated proposed statistic can be computed based on the random sample. The finite sample performance of the statistic is examined in Monte Carlo studies. The method is applied to two latent variable models used in microeconometrics and financial econometrics.

報(bào)告人: 李勇      教授    博導(dǎo)    教育部青年

時(shí)  間: 2018-04-08    15:30

地  點(diǎn): 競慧東302

舉辦單位: 統(tǒng)計(jì)與數(shù)學(xué)學(xué)院  澄園書院