JSM 2015 Online Program

Online Program Home
My Program

Abstract Details

Activity Number: 339
Type: Invited
Date/Time: Tuesday, August 11, 2015 : 10:30 AM to 12:20 PM
Sponsor: International Society for Bayesian Analysis (ISBA)
Abstract #314637 View Presentation
Title: Confidence Distribution (CD) as a Unifying Framework for BFF Inference
Author(s): Regina Y. Liu* and Minge Xie
Companies: Rutgers University and Rutgers University
Keywords: confidence distribution ; fiducial inference ; Bayesian inference ; frequentist inference ; BFF

A confidence distribution (CD) is a sample-dependent distribution function that can serve as a distribution estimate, contrasting with point or interval estimate, of a unknown parameter. It can represent confidence intervals of all levels for the parameter. It can provide "simple and interpretable summaries of what can reasonably be learned from data (and an assumed model)", as well as meaningful answers for all questions in statistical inference. An emerging theme from recent developments on CD is "Any statistical approach, regardless of being frequentist, fiducial or Bayesian (BFF), can potentially be unified under the concept of confidence distributions, as long as it can be used to derive confidence intervals of all levels, exactly or asymptotically." We articulate the logic behind the developments, and show how CD can potentially serve as a unifying framework for all BFF inferences in all aspects, including estimation, testing and prediction. Moreover, we present several examples to show that these developments in CD actually lead to useful inference tools for statistical problems where methods with desirable properties have not been available or could not be easily obtained.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program

For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home