VB_FCBrainMap {BayesBrainMap} | R Documentation |
VB_FCBrainMap
Description
VB Algorithm for FC Bayesian brain map
Usage
VB_FCBrainMap(
prior_mean,
prior_var,
prior_FC,
method_FC = c("VB1", "VB2"),
nsamp_u = 10000,
CI_FC = 0.95,
return_FC_samp = FALSE,
prior_params = c(0.001, 0.001),
BOLD,
TR = NULL,
A0,
S0,
S0_var,
maxiter = 100,
miniter = 3,
epsilon = 0.001,
usePar = FALSE,
PW = FALSE,
seed = 1234,
verbose = FALSE
)
Arguments
prior_mean |
( |
prior_var |
( |
prior_FC |
(list) Parameters of functional connectivity prior. |
method_FC |
Variational Bayes (VB) method for FC Bayesian brain mapping:
|
nsamp_u |
For VB1, the number of samples to generate from u ~ Gamma, where
A is Gaussian conditional on u. Default: |
CI_FC |
Level of posterior credible interval to construct for each FC element.
Default: |
return_FC_samp |
Should the FC samples ( |
prior_params |
Alpha and beta parameters of IG prior on |
BOLD |
( |
A0 , S0 , S0_var |
Initial guesses at latent variables: |
maxiter |
Maximum number of VB iterations. Default: |
miniter |
Minimum number of VB iterations. Default: |
epsilon |
Smallest proportion change in parameter estimates between iterations.
Default: |
usePar |
Parallelize the computation? Default: |
PW |
Prewhiten to account for residual autocorrelation? Default: |
seed |
(Only applicable if |
verbose |
If |
Value
A list of computed values, including the final parameter estimates.