Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149680 | Journal of Statistical Planning and Inference | 2009 | 11 Pages |
Abstract
In this paper we discuss constructing confidence intervals based on asymptotic generalized pivotal quantities (AGPQs). An AGPQ associates a distribution with the corresponding parameter, and then an asymptotically correct confidence interval can be derived directly from this distribution like Bayesian or fiducial interval estimates. We provide two general procedures for constructing AGPQs. We also present several examples to show that AGPQs can yield new confidence intervals with better finite-sample behaviors than traditional methods.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Shifeng Xiong, Weiyan Mu,