View source: R/EM_templateICA.R
LL2_kappa | R Documentation |
Compute part of log-likelihood involving kappa (or kappa_q) for numerical optimization
LL2_kappa(
kappa,
Amat,
Fmat,
Gmat,
GFinvG,
OplusW,
u,
v,
C1 = 1/(4 * pi),
Q = NULL
)
kappa |
Value of kappa for which to compute log-likelihood |
Amat |
Mesh projection matrix |
Fmat |
Matrix used in computation of SPDE precision |
Gmat |
Matrix used in computation of SPDE precision |
GFinvG |
Matrix used in computation of SPDE precision |
OplusW |
Sparse matrix containing estimated values of RHS of trace in part 2 of log-likelihood. In common smoothness model, represents the sum over q=1,...,Q. |
u |
Vector needed for part 3 of log-likelihood |
v |
Vector needed for part 3 of log-likelihood |
C1 |
For the unit variance case, |
Q |
Equal to the number of ICs for the common smoothness model, or NULL for the IC-specific smoothness model |
This is the function to be maximized in order to determine the MLE for \kappa
or the \kappa_q
's in the M-step of the EM algorithm in spatial
template ICA. In the model where \kappa_q
can be different for each IC q
, the optimization function factorizes over the \kappa_q
's. This function computes
the value of the part of the optimization function pertaining to one of the \kappa_q
's.
Value of log-likelihood at logkappa
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