Get_R_new

Inverse range parameters.

beta_delta

nugget parameters.

eta_delta

A List of matrices where the j-th matrix is an absolute difference matrix of the j-th input vector.

Type of kernel. <code>matern_3_2</code> and <code>matern_5_2</code> are <code>Matern kernel</code> with roughness parameter 3/2 and 5/2 respectively. <code>pow_exp</code> is power exponential kernel with roughness parameter alpha. If <code>pow_exp</code> is to be used, one needs to specify its roughness parameter alpha.

kernel_type

Roughness parameters in the kernel functions. It is only useful if the power exponential correlation function is used.

alpha

The inverse of output weights.

inv_output_weights

This function computes the Cholesky decomposition of the correlation matrix in GaSP.

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) <arXiv:1707.08215>, Mengyang Gu, Fangzheng Xie and Long Wang (2021) <arXiv:1807.03829>, Mengyang Gu, Kyle Anderson and Erika McPhillips (2021) <arXiv:1810.11664>.

Mengyang Gu

RobustCalibration

Robust Calibration of Imperfect Mathematical Models

Get_R_new function

<dl> <dt>beta_delta</dt>
<dd>
Inverse range parameters.</dd> <dt>eta_delta</dt>
<dd>
nugget parameters.</dd> <dt>R0</dt>
<dd>
A List of matrices where the j-th matrix is an absolute difference matrix of the j-th input vector.</dd> <dt>kernel_type</dt>
<dd>
Type of kernel. <code>matern_3_2</code> and <code>matern_5_2</code> are <code>Matern kernel</code> with roughness parameter 3/2 and 5/2 respectively. <code>pow_exp</code> is power exponential kernel with roughness parameter alpha. If <code>pow_exp</code> is to be used, one needs to specify its roughness parameter alpha.</dd> <dt>alpha</dt>
<dd>
Roughness parameters in the kernel functions. It is only useful if the power exponential correlation function is used.</dd> <dt>inv_output_weights</dt>
<dd>
The inverse of output weights.</dd></dl>

Arguments

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

Author


Cholesky decomposition of the correlation matrix in GaSP. — Get_R_new

<dl>

 <dt>beta_delta</dt>
<dd>
Inverse range parameters.</dd>

 <dt>eta_delta</dt>
<dd>
nugget parameters.</dd>

 <dt>R0</dt>
<dd>
A List of matrices where the j-th matrix is an absolute difference matrix of the j-th input vector.</dd>

 <dt>kernel_type</dt>
<dd>
Type of kernel. <code>matern_3_2</code> and <code>matern_5_2</code> are <code>Matern kernel</code> with roughness parameter 3/2 and 5/2 respectively. <code>pow_exp</code> is power exponential kernel with roughness parameter alpha. If <code>pow_exp</code> is to be used, one needs to specify its roughness parameter alpha.</dd>

 <dt>alpha</dt>
<dd>
Roughness parameters in the kernel functions. It is only useful if the power exponential correlation function is used.</dd>

 <dt>inv_output_weights</dt>
<dd>
The inverse of output weights.</dd>



</dl>

Get_R_new: Cholesky decomposition of the correlation matrix in GaSP.

Description

Usage

Value

Arguments

Author