gram

The computer model test function introduced in Gramacy et. al 2016.

A suite of computer model test functions that can be used to test and evaluate algorithms for Bayesian (also known as sequential) optimization. Some of the functions have known functional forms, however, most are intended to serve as black-box functions where evaluation requires running computer code that reveals little about the functional forms of the objective and/or constraints. The primary goal of the package is to provide users (especially those who do not have access to real computer models) a source of reproducible and shareable examples that can be used for benchmarking algorithms. The package is a living repository, and so more functions will be added over time. For function suggestions, please do contact the author of the package.

Tony Pourmohamad

CompModels

Pseudo Computer Models for Optimization

gram function

<dl><dt>x1</dt>
<dd>A scalar value between 0 and 1, inclusive</dd>
<dt>x2</dt>
<dd>A scalar value between 0 and 1, inclusive</dd></dl>

Arguments

The Gramacy et. al 2016 test function — gram

<dl>

<dt>x1</dt>
<dd>A scalar value between 0 and 1, inclusive</dd>


<dt>x2</dt>
<dd>A scalar value between 0 and 1, inclusive</dd>

</dl>

gram: The Gramacy et. al 2016 test function

Description

Usage

Value

Arguments

References

Examples