GP.std.grids {BayesGPfit}

Compute the standardized grids

Description

Compute the standardized grids

Usage

GP.std.grids(
  grids,
  center = apply(grids, 2, mean),
  scale = NULL,
  max_range = 6
)

Arguments

grids

A matrix where rows represent grid points and columns are coordinates.

center

A vector of real numbers specifying the centroid parameters in the modified exponential squared kernel. The default value is NULL and set to the center of the grid points: apply(x,2,mean).

scale

A vector of positive numbers specifying the scale parameters in the modified exponential squared kernel. The default value is NULL and set to values such that grid points in a range of (-max_range,max_range) in each dimension.

max_range

A positive real number indicating the maximum range of the grid points to specify the scale parameter. The default value is NULL and set to 6.

Value

A matrix where rows represent the standardized grids.

Author(s)

Jian Kang <[e-mail]>

Examples

library(BayesGPfit)
grids = GP.generate.grids(d=2L)
std_grids = GP.std.grids(grids)
plot(grids[,1],std_grids[,1],asp=1,type="l")
abline(a=0,b=1,lty=2)