This function samples a vector of the model discrepancy for the scenario with multiple sources and measurement bias.
Sample_delta(cov_inv_all, tilde_output_cur, param, p_x,
num_sources, num_obs, rand_norm)A vector of samples of model discrepancy.
a list of inverse covariances of discrepancy and measurement bias.
a list of transformed observations.
a list of the current parameters values in MCMC.
a list of dimensions of the observable inputs.
the number of sources.
the number of observations.
the vector of i.i.d. standard normal samples.
tools:::Rd_package_author("RobustCalibration")
Maintainer: tools:::Rd_package_maintainer("RobustCalibration")
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.