separable_kernel

Function to construct the product correlation matrix with the product form.

internal

Robust parameter estimation and prediction of Gaussian stochastic
process emulators. It allows for robust parameter estimation and prediction using
Gaussian stochastic process emulator. It also implements the parallel partial
Gaussian stochastic process emulator for computer model with massive outputs
See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics;
Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics.

Mengyang Gu

RobustGaSP

Robust Gaussian Stochastic Process Emulation

Jesus Palomo

James Berger

separable_kernel function

<dl> <dt>R0</dt>
<dd>
A List of matrix where the j-th matrix is an absolute difference matrix of the j-th input vector.</dd> <dt>beta</dt>
<dd>
The range parameters.</dd> <dt>kernel_type</dt>
<dd>
A vector specifying the type of kernels of each coordinate of the input. <code>matern_3_2</code> and <code>matern_5_2</code> are <code>Matern correlation</code> with roughness parameter 3/2 and 5/2 respectively. <code>pow_exp</code> is power exponential correlation with roughness parameter alpha. If <code>pow_exp</code> is to be used, one needs to specify its roughness parameter alpha. The default choice is <code>matern_5_2</code>. The <code>periodic_gauss</code> means the Gaussian kernel with periodic folding method with be used. The <code>periodic_exp</code> means the exponential kernel with periodic folding method will be used.</dd>
 <dt>alpha</dt>
<dd>
Roughness parameters in the kernel functions.</dd></dl>

Arguments

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

Author

Product correlation matrix with the product form
 — separable_kernel

<dl>

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

 <dt>beta</dt>
<dd>
The range parameters.</dd>

 <dt>kernel_type</dt>
<dd>
A vector specifying the type of kernels of each coordinate of the input. <code>matern_3_2</code> and <code>matern_5_2</code> are <code>Matern correlation</code> with roughness parameter 3/2 and 5/2 respectively. <code>pow_exp</code> is power exponential correlation with roughness parameter alpha. If <code>pow_exp</code> is to be used, one needs to specify its roughness parameter alpha. The default choice is <code>matern_5_2</code>. The <code>periodic_gauss</code> means the Gaussian kernel with periodic folding method with be used. The <code>periodic_exp</code> means the exponential kernel with periodic folding method will be used.</dd>


 <dt>alpha</dt>
<dd>
Roughness parameters in the kernel functions.</dd>

</dl>

separable_kernel: Product correlation matrix with the product form

Description

Usage

Value

Arguments

Author