log_approx_ref_prior_deriv: Derivative of the jointly robust prior

In RobustGaSP: Robust Gaussian Stochastic Process Emulation

Derivative of the jointly robust prior

Description

The function computes the derivative of the approximate reference prior with regard to inverse range parameter and the nugget-noise ratio parameter (if not fixed). When the nugget is fixed, it only compute the derivative with regard to the inverse range parameter; otherwise it produces derivative with regard to inverse range parameter and noise ratio parameter.

Usage

log_approx_ref_prior_deriv(param, nugget, nugget_est, CL, a, b)

Arguments

param	A vector of natural logarithm of inverse-range parameters and natural logarithm of the nugget-variance ratio parameter.
nugget	The nugget-variance ratio parameter if this parameter is fixed.
nugget_est	Boolean value of whether the nugget is estimated or fixed.
CL	Prior parameter in the jointly robust prior.
a	Prior parameter in the jointly robust prior.
b	Prior parameter in the jointly robust prior.

Value

The numerical value of the derivative of the jointly robust prior with regard to beta (the inverse-range parameters) and nugget (the nugget-variance ratio parameter). When the nugget is fixed, the derivative is on inverse-range parameters.

Author(s)

Mengyang Gu [aut, cre], Jesus Palomo [aut], James Berger [aut]

Maintainer: Mengyang Gu <[e-mail]>

References

M. Gu. (2016). Robust uncertainty quantification and scalable computation for computer models with massive output. Ph.D. thesis. Duke University.

See Also

log_approx_ref_prior,rgasp

RobustGaSP documentation built on June 1, 2022, 9:08 a.m.