Local sensitivity of posterior expectations

成果类型:
Article
署名作者:
Gustafson, P
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
发表日期:
1996
页码:
174-195
关键词:
robust bayesian-analysis priors
摘要:
We investigate the degree to which posterior expectations are sensitive to prior distributions, using a local method based on functional differentiation. Invariance considerations suggest a family of norms which can be used to measure perturbations to the prior. The sensitivity measure is seen to depend heavily on the choice of norm; asymptotic results suggest which norm will yield the most useful results in practice, We find that to maintain asymptotically sensible behaviour, it is necessary to reduce the richness of the class of prior perturbations as the dimension of the parameter space increases. Jeffreys' prior is characterized as the prior to which inference is least sensitive.