deleteGP

deleteGPs

deleteGPsep

deleteGPseps

Frees memory allocated by a particular C-side Gaussian process
 object, or all GP objects currently allocated

 utilities

Performs approximate GP regression for large computer experiments and spatial datasets. The approximation is based on finding small local designs for prediction (independently) at particular inputs. OpenMP and SNOW parallelization are supported for prediction over a vast out-of-sample testing set; GPU acceleration is also supported for an important subroutine. OpenMP and GPU features may require special compilation. An interface to lower-level (full) GP inference and prediction is provided. Wrapper routines for blackbox optimization under mixed equality and inequality constraints via an augmented Lagrangian scheme, and for large scale computer model calibration, are also provided. For details and tutorial, see Gramacy (2016 <doi:10.18637/jss.v072.i01>.

Robert Gramacy

laGP

Local Approximate Gaussian Process Regression

deleteGP function

<dl> <dt>gpi</dt>
<dd>a scalar positive integer specifying an allocated isotropic GP object</dd> <dt>gpsepi</dt>
<dd>similar to <code>gpi</code> but indicating a separable GP object</dd></dl>

Arguments

Robert B. Gramacy <a href="/link/rbg%40vt.edu?package=laGP&version=1.5-9" data-mini-rdoc="laGP::rbg@vt.edu">rbg@vt.edu</a>

Author

Delete C-side Gaussian Process Objects — deleteGP

<dl>

 <dt>gpi</dt>
<dd>a scalar positive integer specifying an allocated isotropic GP object</dd>

 <dt>gpsepi</dt>
<dd>similar to <code>gpi</code> but indicating a separable GP object</dd>

</dl>

Robert B. Gramacy <a href='mailto:rbg@vt.edu'>rbg@vt.edu</a>

deleteGP: Delete C-side Gaussian Process Objects

Description

Usage

Value

Arguments

Author

Details

See Also

Examples