Accept_proposal

Determine whether the proposed poserior sample is accepted at one step of MCMC.

internal

Implements full Bayesian analysis for calibrating mathematical models with new   methodology for modeling the discrepancy function. It allows for emulation, calibration and prediction using complex mathematical model outputs and experimental data. See the reference: Mengyang Gu and Long Wang, 2018, Journal of Uncertainty Quantification; Mengyang Gu, Fangzheng Xie and Long Wang, 2022, Journal of Uncertainty Quantification; Mengyang Gu, Kyle Anderson and Erika McPhillips, 2023, Technometrics.

Mengyang Gu

RobustCalibration

Robust Calibration of Imperfect Mathematical Models

Accept_proposal function

<dl> <dt>r</dt>
<dd>
r is a real number calculated by the ratio of posterior distribution with a new proposed sample of parameters and the posterior distribution with the current parameters.</dd></dl>

Arguments

tools:::Rd_package_author("RobustCalibration")
Maintainer: tools:::Rd_package_maintainer("RobustCalibration")

Author


Determine whether we accept the proposed poserior sample at one step of MCMC. — Accept_proposal

<dl>

 <dt>r</dt>
<dd>
r is a real number calculated by the ratio of posterior distribution with a new proposed sample of parameters and the posterior distribution with the current parameters.</dd>

</dl>

Accept_proposal: Determine whether we accept the proposed poserior sample at one step of MCMC.

Description

Usage

Value

Arguments

Author

References