Log_marginal_post_delta: Natural Logorithm of the posterior of the discrepancy in...

In RobustCalibration: Robust Calibration of Imperfect Mathematical Models

Natural Logorithm of the posterior of the discrepancy in model calibration with multiple sources with measurement bias.

Description

This function compute the natural Logorithm of the posterior assuming the GaSP or S-GaSP models for the discrepancy function.

Usage

Log_marginal_post_delta(param, L, delta,  p_x, CL, a, b)

Arguments

param	current parameters in the MCMC.
L	Cholesky decomposition of the covariance matrix.
delta	a vector of the discrepancy.
p_x	dimension of observable inputs.
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

Natural logorithm of the posterior of the discrepancy function.

Author(s)

Mengyang Gu [aut, cre]

Maintainer: Mengyang Gu <[e-mail]>

References

A. O'Hagan and M. C. Kennedy (2001), Bayesian calibration of computer models, Journal of the Royal Statistical Society: Series B (Statistical Methodology, 63, 425-464.

Mengyang Gu. (2016). Robust Uncertainty Quantification and Scalable Computation for Computer Models with Massive Output. Ph.D. thesis. Duke University.

M. Gu and L. Wang (2017) Scaled Gaussian Stochastic Process for Computer Model Calibration and Prediction. arXiv preprint arXiv:1707.08215.

M. Gu (2018) Jointly Robust Prior for Gaussian Stochastic Process in Emulation, Calibration and Variable Selection . arXiv preprint arXiv:1804.09329.

RobustCalibration documentation built on June 22, 2024, 10:37 a.m.