shapeSlot

Extract the slot of a structure.

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

shapeSlot function

<dl> <dt>object</dt>
<dd></dd>An object to extract from, typically a covariance kernel.
 <dt>slotName</dt>
<dd></dd>Name of the slot to be extracted.
 <dt>type</dt>
<dd></dd>Type of slot to be extracted. Can be either a type of parameter,
 <code>"var"</code> or <code>"all"</code>.
 <dt>as</dt>
<dd></dd>Type of result wanted. Can be <code>"vector"</code>, <code>"list"</code>
 or <code>"matrix"</code>.
</dl>

Arguments

Extract the slot of a structure.

Extracts the Slots of a Structure — shapeSlot

<dl>

 <dt>object</dt>
<dd>

An object to extract from, typically a covariance kernel.
</dd>

 <dt>slotName</dt>
<dd>

Name of the slot to be extracted.
</dd>

 <dt>type</dt>
<dd>

Type of slot to be extracted. Can be either a type of parameter,
 <code>"var"</code> or <code>"all"</code>.
</dd>

 <dt>as</dt>
<dd>

Type of result wanted. Can be <code>"vector"</code>, <code>"list"</code>
 or <code>"matrix"</code>.
</dd>

</dl>

shapeSlot: Extracts the Slots of a Structure

Description

Usage

Value

Arguments