logLikelihoodFun.MLPKriging

Evaluate log-likelihood at given GP theta

Interface to 'libKriging' 'C++' library <https://github.com/libKriging> that should
provide most standard Kriging / Gaussian process regression features
(like in 'DiceKriging', 'kergp' or 'RobustGaSP' packages).
'libKriging' relies on Armadillo linear algebra library (Apache 2 license) by Conrad Sanderson,
'lbfgsb_cpp' is a 'C++' port around by Pascal Have of 'lbfgsb' library (BSD-3 license) by
Ciyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales used for hyperparameters optimization.

Yann Richet

rlibkriging

Kriging Models using the 'libKriging' Library

Pascal Havé

Yves Deville

Conrad Sanderson

Ciyou Zhu

Richard Byrd

Jorge Nocedal

Jose Luis Morales

Mike Smith

logLikelihoodFun.MLPKriging function

<dl><dt>object</dt>
<dd>MLPKriging object</dd>
<dt>theta</dt>
<dd>range parameter vector</dd>
<dt>return_grad</dt>
<dd>return gradient?</dd>
<dt>return_hess</dt>
<dd>return hessian?</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Evaluate log-likelihood at given GP theta — logLikelihoodFun.MLPKriging

<dl>

<dt>object</dt>
<dd>MLPKriging object</dd>


<dt>theta</dt>
<dd>range parameter vector</dd>


<dt>return_grad</dt>
<dd>return gradient?</dd>


<dt>return_hess</dt>
<dd>return hessian?</dd>


<dt>...</dt>
<dd>ignored</dd>

</dl>

Evaluate log-likelihood at given GP theta

logLikelihoodFun.MLPKriging: Evaluate log-likelihood at given GP theta

Description

Usage

Arguments