Fitting data into a required function
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I am trying to fit this data -
x = [0.001 0.01 0.1 1 10];
y = [63.5 74.5 94.1 94.2 103.5];
into a function y = m*x^n
polyfit and lsqcurvefit not seem to be working here
can someone help me?
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Star Strider
2021-2-13
Try this:
x = [0.001 0.01 0.1 1 10];
y = [63.5 74.5 94.1 94.2 103.5];
fcn = @(b,x) b(1).*x.^b(2);
B0 = rand(2,1);
B = lsqcurvefit(fcn, B0, x, y)
figure
plot(x, y, 'p')
hold on
plot(x, fcn(B,x), '-r')
hold off
set(gca, 'XScale','log') % Optional
grid
xlabel('X')
ylabel('Y')
legend('Data', sprintf('y = %.3f\\cdotx^{%.3f}', B), 'Location','E')
.
更多回答（1 个）
randerss simil
2021-2-13
编辑：randerss simil
2021-2-13
%if true
m = 2
n = 1.5
Y = m*x.^n;
k = polyval(x,Y)
First use polyval for the equation and then apply polyfit
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