nsDist: Calculate coordinate-specific distance matrices

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

Description

nsDist calculates x, y, and x-y distances for use in the nonstationary correlation calculation. The sign of the cross-distance is important. The function contains an optional argument for re-scaling the distances such that the coordinates lie in a square.

Usage

nsDist(coords, scale_factor = NULL, isotropic = FALSE)

Arguments

coords	N x 2 matrix; contains the x-y coordinates of stations
scale_factor	Scalar; optional argument for re-scaling the distances.
isotropic	Logical; indicates whether distances should be calculated separately for each coordinate dimension (FALSE) or simultaneously for all coordinate dimensions (TRUE). isotropic = TRUE can only be used for two-dimensional coordinate systems.

Value

A list of distances matrices, with the following components:

dist1_sq	N x N matrix; contains values of pairwise squared distances in the x-coordinate.
dist2_sq	N x N matrix; contains values of pairwise squared distances in the y-coordinate.
dist12	N 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))
# Calculate distances
dist_list <- nsDist(coords)
# Use nsDist to calculate Euclidean distances
dist_Euclidean <- sqrt(nsDist(coords, isotropic = TRUE)$dist1_sq)

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