dmnorm_nngp: Function for the evaluating the NNGP approximate density.

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

Description

dmnorm_nngp (and rmnorm_nngp) calculate the approximate NNGP likelihood for a fixed set of parameters (i.e., A and D matrices). Finally, the distributions must be registered within nimble.

Usage

dmnorm_nngp(x, mean, AD, nID, N, k, log)

Arguments

x	N-vector of data.
mean	N-vector with current values of the mean
AD	N x (k+1) matrix; the first k columns are the 'A' matrix, and the last column is the 'D' vector.
nID	N x k matrix of neighbor indices.
N	Scalar; number of data measurements.
k	Scalar; number of nearest neighbors.
log	Scalar; should the density be on the log scale (1) or not (0).

Value

The NNGP approximate density.

BayesNSGP documentation built on Jan. 9, 2022, 9:07 a.m.