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How can I calculate the empircal CDF from an empirical PDF when dimensions are greater than 2?

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Greg
Greg on 28 Jul 2014
Commented: Greg on 23 Feb 2018
I would like to calculate the empirical cumulative distribution of a data set with more than 2 dimensions. The only examples I have been able to find are for bivariate data (using hist3 and cumsum). Below is an example 3 dimensional PDF. I would like a robust solution that can accommodate any number of dimensions, if possible. Any help would be very much appreciated. Thank you.
sPDF(1,1,1) = 1;
sPDF(2,1,1) = 2;
sPDF(1,2,1) = 3;
sPDF(2,2,1) = 4;
sPDF(1,1,2) = 5;
sPDF(2,1,2) = 6;
sPDF(1,2,2) = 7;
sPDF(2,2,2) = 8;

Accepted Answer

Star Strider
Star Strider on 28 Jul 2014
See if the mvncdf function and its friends do what you want.
  10 Comments
Greg
Greg on 23 Feb 2018
You could try interpolating the NaN values first. Something like the following: inpaint This one may also work: inpainting Or you could try fitting a neural network to the data and predict those NaN values.

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