parNamesSymm

Vector of names for the general 'Symm' parameterisation.

Gaussian process regression with an emphasis on kernels.
Quantitative and qualitative inputs are accepted. Some pre-defined
kernels are available, such as radial or tensor-sum for
quantitative inputs, and compound symmetry, low rank, group kernel
for qualitative inputs. The user can define new kernels and
composite kernels through a formula mechanism. Useful methods
include parameter estimation by maximum likelihood, simulation,
prediction and leave-one-out validation.

Olivier Roustant

kergp

Gaussian Process Laboratory

parNamesSymm function

<dl><dt>nlev</dt>
<dd>Number of levels.</dd></dl>

Arguments

Vector of Names for the General 'Symm' Parameterisation — parNamesSymm

<dl>

<dt>nlev</dt>
<dd>Number of levels.</dd>

</dl>

parNamesSymm: Vector of Names for the General 'Symm' Parameterisation

Description

Usage

Value

Arguments

Examples