# demgpard

## Purpose

Demonstrate ARD using a Gaussian Process.

## Synopsis

    demgpare

## Description

The data consists of three input variables `x1`, `x2` and `x3`, and one target variable `t`. The target data is generated by computing `sin(2*pi*x1)` and adding Gaussian noise, x2 is a copy of x1 with a higher level of added noise, and x3 is sampled randomly from a Gaussian distribution. A Gaussian Process, is trained by optimising the hyperparameters using the scaled conjugate gradient algorithm. The final values of the hyperparameters show that the model successfully identifies the importance of each input.

## See Also

`demgp`, `gp`, `gperr`, `gpfwd`, `gpgrad`, `gpinit`, `scg`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)