Find confidence interval in bivariate kernel estimation using ksdensity

2017 2 17

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I'm executing this piece of code in order to estimate the probability density function of a bivariate set of random points:

x = [0+.5*rand(20,1) 5+2.5*rand(20,1);
      .75+.25*rand(10,1) 8.75+1.25*rand(10,1)];
figure
ksdensity(x);

and I wonder how to use the informations coming from the Matlab function ksdensity to evaluate the confidence interval I need.

My goal is to find outliers points in the set, namely that points that fall over the confidence interval.

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Hi Daniele, I have the same problem, have you found a solution to it?Thank you.

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