fast_Gp_sim: Approximate GP simulation

In joeguinness/GpGp: Fast Gaussian Process Computation Using Vecchia's Approximation

Approximate GP simulation

Description

Calculates an approximation to the inverse Cholesky factor of the covariance matrix using Vecchia's approximation, then the simulation is produced by solving a linear system with a vector of uncorrelated standard normals

Usage

fast_Gp_sim(covparms, covfun_name = "matern_isotropic", locs, m = 30)

Arguments

covparms	A vector of covariance parameters appropriate for the specified covariance function
covfun_name	See GpGp for information about covariance functions.
locs	matrix of locations. Row i of locs specifies the location of element i of y, and so the length of y should equal the number of rows of locs.
m	Number of nearest neighbors to use in approximation

Value

vector of simulated values

Examples

locs <- as.matrix( expand.grid( (1:50)/50, (1:50)/50 ) )
y <- fast_Gp_sim(c(4,0.2,0.5,0), "matern_isotropic",  locs, 30 )
fields::image.plot( matrix(y,50,50) )

joeguinness/GpGp documentation built on Feb. 22, 2024, 9:43 a.m.