.findTheta {BayesfMRI}

Perform the EM algorithm of the Bayesian GLM fitting

Description

Perform the EM algorithm of the Bayesian GLM fitting

Usage

.findTheta(theta, spde, y, X, QK, Psi, A, Ns, tol, verbose = FALSE)

Arguments

theta

the vector of initial values for theta

spde

a list containing the sparse matrix elements Cmat, Gmat, and GtCinvG

y

the vector of response values

X

the sparse matrix of the data values

QK

a sparse matrix of the prior precision found using the initial values of the hyperparameters

Psi

a sparse matrix representation of the basis function mapping the data locations to the mesh vertices

A

a precomputed matrix crossprod(X%*%Psi)

Ns

the number of columns for the random matrix used in the Hutchinson estimator

tol

a value for the tolerance used for a stopping rule (compared to the squared norm of the differences between theta(s) and theta(s-1))

verbose

(logical) Should intermediate output be displayed?