nsCrossdist: Calculate coordinate-specific cross-distance matrices

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

Description

nsCrossdist calculates coordinate-specific cross distances in x, y, and x-y for use in the nonstationary cross-correlation calculation. This function is useful for calculating posterior predictions.

Usage

nsCrossdist(coords, Pcoords, scale_factor = NULL, isotropic = FALSE)

Arguments

coords	N x 2 matrix; contains x-y coordinates of station (observed) locations.
Pcoords	M x 2 matrix; contains x-y coordinates of prediction locations.
scale_factor	Scalar; optional argument for re-scaling the distances.
isotropic	Logical; indicates whether distances should be calculated using Euclidean distance (isotropic = TRUE) or using the anisotropic formulation (isotropic = FALSE).

Value

A list of distances matrices, with the following components:

dist1_sq	M x N matrix; contains values of pairwise squared cross- distances in the x-coordinate.
dist2_sq	M x N matrix; contains values of pairwise squared cross- distances in the y-coordinate.
dist12	M x N matrix; contains values of pairwise signed cross- distances between the x- and y-coordinates.
scale_factor	Value of the scale factor used to rescale distances.

Examples

# Generate some coordinates 
coords <- cbind(runif(100),runif(100))
Pcoords <- cbind(runif(200),runif(200))
# Calculate distances
Xdist_list <- nsCrossdist(coords, Pcoords)

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