Bayesian Statistics Seminar
North Carolina State University


NAME: Dr. Jan Hannig



Generalized Fiducial Inference and Confidence Distributions


A. Fisher's fiducial inference has been the subject of many discussions
and controversies ever since he introduced the idea during the 1930's.
The idea experienced a bumpy ride, to say the least, during its early
years and one can safely say that it eventually fell into disfavor
among mainstream statisticians. However, it appears to have made a
resurgence recently under various names and modifications. For example
under the new name generalized inference fiducial inference has proved
to be a useful tool for deriving statistical procedures for problems
where frequentist methods with good properties were previously
unavailable. Therefore we believe that the fiducial argument of R.A.
Fisher deserves a fresh look from a new angle.
In this talk we first generalize Fisher's fiducial argument and obtain a fiducial recipe applicable in virtually any situation. We demonstrate this fiducial recipe on examples of varying complexity.
 We also investigate, by simulation and by theoretical considerations, some properties of the statistical procedures derived by the fiducial recipe showing they often
posses good repeated sampling, frequentist properties. Finally, we show how a generalized fiducial inference paradigm can be used to combine confidence distributions.

Portions of this talk are based on a joined work with Hari Iyer,
 Thomas C.M. Lee, Randy Lai and Min-ge Xie.

Thursday, 24 October 2013

4:15 - 5:15 pm

1216 SAS Hall