plot.simulate.gp

Function to plot simulations from a <code>gp</code> object.

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

plot.simulate.gp function

<dl> 
 <dt>x</dt>
<dd></dd>An object containing simulations, produced by 'simulate' with
 <code>output = "list"</code>.
 <dt>y</dt>
<dd></dd>Not used yet.
 <dt>col</dt>
<dd></dd>Named list of colors to be used, with elements <code>"sim"</code> and
 <code>"trend"</code>.
 <dt>show</dt>
<dd></dd>A logical vector telling which elements must be shown.
 <dt>...</dt>
<dd></dd>Further argument passed to <code>plot</code>.
 
</dl>

Arguments

Function to plot simulations from a <code>gp</code> object.

Plot Simulations from a gp Object — plot.simulate.gp

<dl>

 
 <dt>x</dt>
<dd>

An object containing simulations, produced by 'simulate' with
 <code>output = "list"</code>.
</dd>

 <dt>y</dt>
<dd>

Not used yet.
</dd>

 <dt>col</dt>
<dd>

Named list of colors to be used, with elements <code>"sim"</code> and
 <code>"trend"</code>.
</dd>

 <dt>show</dt>
<dd>

A logical vector telling which elements must be shown.
</dd>

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

Further argument passed to <code>plot</code>.
</dd>

 
</dl>

plot.simulate.gp: Plot Simulations from a `gp` Object

Description

Usage

Value

Arguments

See Also