gpOptimise: Optimise the inducing variable based kernel.

In gptk: Gaussian Processes Tool-Kit

Description

optimises the Gaussian process model for a given number of iterations.

Usage

gpOptimise(model, display, iters, gradcheck)

Arguments

model	the model to be optimised.
display	whether or not to display while optimisation proceeds, set to 2 for the most verbose and 0 for the least verbose.
iters	number of iterations for the optimisation.
gradcheck	(logical) do a gradient check.

Value

model

the optimised model.

See Also

gpCreate, gpGradient, gpObjective.

Examples

## missing

Example output

Loading required package: Matrix
Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.1-1 (2017-07-02) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: 'spam'

The following objects are masked from 'package:base':

    backsolve, forwardsolve

Loading required package: maps

gptk documentation built on May 2, 2019, 3:27 p.m.