On an inferential model construction using generalized associations
arXiv:1511.06733 · doi:10.1016/j.jspi.2016.11.006
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 than the basic IM 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.
18 pages, 4 figures
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