Multivariate kernel density estimation: Difference between revisions

Revision as of 07:20, 15 October 2015

Revision as of 10:09, 25 November 2015

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We consider estimating the density of the Gaussian mixture

{{nowrapmath|(4''π'')⁻¹ exp(−{{frac|2}} (''x''₁² + ''x''₂²))

+ (4''π'')⁻¹ exp(−{{frac|2}} ((''x''₁ - 3.5)² + ''x''₂²))}},

from 500 randomly generated points. We employ the Matlab routine for

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<source lang="matlab" style="overflow:auto;">

clear all

% generate synthetic data

data=[randn(500,2);

randn(500,1)+3.5, randn(500,1);];

% call the routine, which has been saved in the current directory

[bandwidth,density,X,Y]=kde2d(data);

% plot the data and the density estimate

contour3(X,Y,density,50), hold on

plot(data(:,1),data(:,2),'r.','MarkerSize',5)

</source>