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Inferential Models
book

Inferential Models

by Ryan Martin, Chuanhai Liu
September 2015
Intermediate to advanced content levelIntermediate to advanced
276 pages
9h 7m
English
Chapman and Hall/CRC
Content preview from Inferential Models
16 PRELIMINARIES
to use the “conditional distribution” of Z, given X = x, for the prediction problem.
However, given X = x, the distribution of Z is degenerate, i.e., Z = x θ with prob-
ability 1. Since θ is unknown, this distribution is unknown, so Z is not conditionally
predictable. See the relevant section on fiducial inference in Chapter 2 for more dis-
cussion of this point. The remaining option is to use the “marginal distribution” of Z
for the prediction problem. That is, perform the prediction step based on the N(0, 1)
model, ignoring X entirely. This is the approach we advocate throughout the book.
Toward inference on θ, consider an interval assertion of the form
A = A
θ
0
,δ
= [θ
0
δ ,θ
0
+ δ ],
where θ
0
R and δ 0 are specified values. From the ...
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Publisher Resources

ISBN: 9781439886519