dmnorm_gp2Scale: Function for the evaluating the Gaussian likelihood with...

In BayesNSGP: Bayesian Analysis of Non-Stationary Gaussian Process Models

Function for the evaluating the Gaussian likelihood with gp2Scale sparse covariance.

Description

dmnorm_gp2Scale (and rmnorm_gp2Scale) calculate the usual Gaussian likelihood for a fixed set of parameters (but with sparse matrices). Finally, the distributions must be registered within nimble.

Usage

dmnorm_gp2Scale(x, mean, Cov, N, Nnz, log = 1)

Arguments

x	Vector of measurements
mean	Vector of mean values
Cov	Matrix of size N x N; sparse kernel
N	Number of measurements in x
Nnz	Number of measurements in x
log	Logical; should the density be evaluated on the log scale.

Value

Returns the Gaussian likelihood using the gp2Scale sparse covariance.

BayesNSGP documentation built on Dec. 11, 2025, 5:08 p.m.