loglik_kappa_est: Kappa log-likelihood

In BayesBrainMap: Estimate Brain Networks and Connectivity with Population-Derived 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 (prior standard deviations)
mesh	Object of class "BrainMap_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 networks for the common smoothness model, or NULL for the network-specific smoothness model

Details

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

Value

Value of negative log likelihood

BayesBrainMap documentation built on Aug. 8, 2025, 7:25 p.m.