EM_FCtemplateICA {templateICAr} | R Documentation |
EM Template ICA
Description
EM Algorithm for FC Template ICA Model
Usage
EM_FCtemplateICA(
template_mean,
template_var,
template_FC,
prior_params = c(0.001, 0.001),
BOLD,
AS_0,
maxiter = 100,
miniter = 3,
epsilon = 0.001,
Gibbs_nsamp = 1000,
Gibbs_nburn = 50,
Gibbs_nchain = 10,
eps_inter = NULL,
verbose
)
Arguments
template_mean |
( |
template_var |
( |
template_FC |
(list) Parameters of functional connectivity template |
prior_params |
Alpha and beta parameters of IG prior on tau^2 (error variance) |
BOLD |
( |
AS_0 |
(list) initial guess at latent variables: A ( |
maxiter |
Maximum number of EM iterations. Default: |
miniter |
Minimum number of EM iterations. Default: |
epsilon |
Smallest proportion change in log-posterior between iterations.
Default: |
Gibbs_nsamp |
the number of Gibbs posterior samples of A and S to output after burn-in |
Gibbs_nburn |
the number of Gibbs posterior samples of A and S to throw away before saving |
Gibbs_nchain |
the number of simultaneous Gibbs chains to run |
eps_inter |
Intermediate values of epsilon at which to save results (used
to assess benefit of more stringent convergence rules). Default:
|
verbose |
If |
Details
EM_FCtemplateICA
implements the expectation-maximization
(EM) algorithm for the functional connectivity (FC) template ICA model
Value
A list of computed values, including the final parameter estimates.