exponential_scaledim: Exponential covariance function, different range parameter...

Description Usage Arguments Value Functions Parameterization

View source: R/RcppExports.R

Description

From a matrix of locations and covariance parameters of the form (variance, range_1, ..., range_d, nugget), return the square matrix of all pairwise covariances.

Usage

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exponential_scaledim(covparms, locs)

d_exponential_scaledim(covparms, locs)

Arguments

covparms

A vector with covariance parameters in the form (variance, range_1, ..., range_d, nugget)

locs

A matrix with n rows and d columns. Each row of locs is a point in R^d.

Value

A matrix with n rows and n columns, with the i,j entry containing the covariance between observations at locs[i,] and locs[j,].

Functions

Parameterization

The covariance parameter vector is (variance, range_1, ..., range_d, nugget). The covariance function is parameterized as

M(x,y) = σ^2 exp( - || D^{-1}(x - y) || )

where D is a diagonal matrix with (range_1, ..., range_d) on the diagonals. The nugget value σ^2 τ^2 is added to the diagonal of the covariance matrix. NOTE: the nugget is σ^2 τ^2 , not τ^2 .


GpGp documentation built on June 10, 2021, 1:07 a.m.