loglik_kappa_est: Kappa log-likelihood

In templateICAr: Estimate Brain Networks and Connectivity with ICA and Empirical Priors

Kappa log-likelihood

Description

Applicable to a single latent field, or multiple latent fields if common smoothness is assumed

Usage

loglik_kappa_est(par, delta, D_diag, mesh, C1 = 1/(4 * pi), Q = NULL)

Arguments

par	Vector of length two containing values of log kappa and log residual variance at which to compute log likelihood
delta	Estimate of delta (subject effect or deviation)
D_diag	Diagonal values of D matrix (template standard deviations)
mesh	Object of class "templateICA_mesh" containing the triangular mesh (see make_mesh)
C1	For the unit variance case, \tau^2 = C1/\kappa^2, where C1 = 1/(4\pi) when \alpha=2, \nu=1, d=2
Q	Equal to the number of ICs for the common smoothness model, or NULL for the IC-specific smoothness model

Details

Compute log-likelihood of kappa given an initial estimate of delta

Value

Value of negative log likelihood

templateICAr documentation built on April 3, 2025, 7:41 p.m.