Next: Autoregressive Parameter Priors
Up: Small Scale Variation
Previous: STSAR model in FMRI
Note that from equations 1 and 2
with , our data, , is related to our
spatio-temporal noise process, , by:
|
(11) |
where is the signal component. This equation, along with
equations 7, 8 and 9,
describes our likelihood,
. We now
need to specify the priors on the noise parameters
. For this
we assume independence between the priors for these parameters,
i.e.
. It is worth
noting that assuming independence in the prior does not impose
independence between the same parameters in the posterior distribution.