given that you have this line of code how do you count the number of points in each quadrant ?

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Classical = pdist2(matrix_logdiff_nsample, mean(matrix_logdiff_nsample),'mahal');
p = size(matrix_logdiff_nsample,2);
chi2quantile = chi2inv(0.99,p);
[SFmcd, MFmcd, Fmcd, OutFmcd] = robustcov(matrix_logdiff_nsample);
plot(Classical, Fmcd, 'o')
line([chi2quantile, chi2quantile], [0, 120], 'color', 'r')
line([0, 80], [chi2quantile, chi2quantile], 'color', 'r')
hold on
plot(Classical(OutFmcd), Fmcd(OutFmcd), 'b*')
xlabel('Mahalanobis Distance')
ylabel('Robust Distance')
title('Distance Plot, Fast MCD method')

Akzeptierte Antwort

Adam Danz
Adam Danz am 12 Jul. 2020
Bearbeitet: Adam Danz am 13 Jul. 2020
You just need to modify either of the two answers received for similar questions in the past (listed under your question).
To modify this answer, you just need to replace the centerPoint_x, centerPoint_y values with the coordinates you're using to define the quadrants.
Based on your image it would look something like,
centerPoint_x = 15; % approximate guess based on image
centerPoint_y = 18; % approximate guess based on image
  5 Kommentare
Adam Danz
Adam Danz am 13 Jul. 2020
Bearbeitet: Adam Danz am 15 Jul. 2020
You need to exchange "x" and "Y" with whatever values you're using to define the center point. Don't just copy-paste without doing the thinking.

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