# Gaussian Mixture Random variables Set (tutorial)

The Gaussian Mixture Random Variable Set allows to fit experimental data using kernel smoothing in dimension one or above.

## Input data

In this tutorial, a distribution with two variables is considered. The samples from the distribution are imported from an ASCII file.

Samples from a two-dimensional distribution

## Creation of the object

A new Random Variable Set has to be created. The option *Import data from CSV file for Gaussian Mixture Random variables Set* is selected.

The input file is selected using *browse*. The data must be organised in columns separated by a tabulation, space, colon or semicolon. Each column correspond to one dimension.
Once the file is added, click on *Next*, a preview of the data used to create the Gaussian Mixture Random Variable Set is shown.

In this example, the data in the ASCII are comma separated. Choose the comma as a separator to display the values.

The coordinates of the distribution must be given a name. In this example, *x* denotes the first coordinate and *y* denotes the second coordinate.
Note that the name attributed to the variables must not be already worn by another object in the project.

Click then on on *Next*, the editor of the Gaussian Mixture Random variables Set appears.

The tab *Random Variables* shows the Random Variables which have been created, associated with the Gaussian Mixture Random Variable Set.
The tab *Correlation* shows the correlation matrix associated with the different Random Variables.
The tab *Central points* shows the coordinates of the central points used for kernel smoothing.

## Plot the data

The probability density function associated with the Random Variables can be displayed by clicking on *Show preview*. The aspect is the following: