zeta_fun: Function to compute zeta_{ijk} (independent case) and...

In vicvolodina93/linkedEmulation: Compute mean and variance of the linked emulator

Function to compute ζ_{ijk} (independent case) and ζ_{ij} (dependent case) of integrated emulator with a squared exponential kernel.

Description

Function to compute ζ_{ijk} (independent case) and ζ_{ij} (dependent case) of integrated emulator with a squared exponential kernel.

Usage

zeta_fun(
  w_i,
  w_j,
  mu,
  Sigma,
  params,
  ind = "TRUE",
  det_comp = NULL,
  Gamma.inv = NULL,
  GS.inv = NULL
)

Arguments

w_i	a vector of size k.
w_j	a vector of size k.
mu	a vector of predictive mean values of length k.
Sigma	a variance-covariance matrix.
params	a list with parameter values.
ind	logical indicating if we adopt independence assumption.
det_comp	a determinant component in the calculations.
Gamma.inv	an inverse of Gamma matrix.
GS.inv	an inverse of the sum of covariance matrix and Gamma.

Value

a vector (independent case) or a single value (dependent case).

vicvolodina93/linkedEmulation documentation built on July 7, 2022, 1:25 a.m.