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scientificComputing/statistics/exercises/mlepropfit.m

32 lines
628 B
Matlab

m = 2.0; % slope
sigma = 1.0; % standard deviation
n = 100; % number of data pairs
% data pairs:
x = 5.0*rand(n, 1);
y = m*x + sigma*randn(n, 1);
% fit:
slope = mleslope(x, y);
fprintf('slopes:\n');
fprintf('original = %.2f\n', m);
fprintf(' fit = %.2f\n', slope);
% lines:
xx = 0.0:0.1:5.0; % x-axis values
yorg = m*xx;
yfit = slope*xx;
% plot:
plot(xx, yorg, '-r', 'linewidth', 5);
hold on;
plot(xx, yfit, '-g', 'linewidth', 2);
plot(x, y, 'ob');
hold off;
legend('data', 'original', 'fit', 'Location', 'NorthWest');
legend('boxoff')
xlabel('x');
ylabel('y');
savefigpdf(gcf, 'mlepropfit.pdf', 12, 7);