Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7547247 | Journal of Statistical Planning and Inference | 2018 | 11 Pages |
Abstract
The inferential model (IM) approach, like fiducial and its generalizations, depends on a representation of the data-generating process. Here, a particular variation on the IM construction is considered, one based on generalized associations. The resulting generalized IM is more flexible in that it does not require a complete specification of the data-generating process and is provably valid under mild conditions. Computation and marginalization strategies are discussed, and two applications of this generalized IM approach are presented.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Ryan Martin,