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Given that you have the code below, how do you write a code to count the number of points in each quadrant with the attached data set

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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')
  2 Comments
Walter Roberson
Walter Roberson on 12 Jul 2020
For any given point, what are its coordinates based upon the file or variable -- coordinates in the same terms as what is being divided for the purpose of quadrants?
Is the division into quadrants to be based upon half-way through the span of values that appear (mean)? Is it to be based upon median? Is it to be based upon some absolute coordinates (e.g., 0 to 50 and 50 to 100, even if the mean or median might be closer to 70?)

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Answers (1)

Walter Roberson
Walter Roberson on 12 Jul 2020
Supposing your two variables are named v1 and v2, then
counts = accumarray([1+(v1(:)>=mean(v1)), 1+(v2(:)>=mean(v2))], 1, [2 2]);

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