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Statistical Computing in Nuclear Imaging
book

Statistical Computing in Nuclear Imaging

by Arkadiusz Sitek
December 2014
Intermediate to advanced content levelIntermediate to advanced
275 pages
9h 12m
English
CRC Press
Content preview from Statistical Computing in Nuclear Imaging
184 Statistical Computing in Nuclear Imaging
the J effreys prior such invariance under reparametrizatio n and an in
terested
reader should consult the classical works of Jeffreys [49] and Lehmann and
Casella [66].
Since the assumption of f
i
for each voxel implies the Poisson distribution,
the Fisher information for 1D Poisson process is equal to (f
i
)
1
. It follows
that the Jeffreys prior is the square root of this value and equal to
p
J
(f)
I
Y
i=1
(f
i
)
1
2
(6.15)
The proportionality sign is used because the prior is improper and the distri-
bution of the prior cannot be norma lized to 1. Again using Poisson distribution
(Equation (6.11)) and marginalizing f
i
’s ...
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Publisher Resources

ISBN: 9781439849347