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How can I fit a curve to x, y points and obtain the regression?

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Sarah on 19 Nov 2018
Commented: Sarah on 20 Nov 2018
I have plotted x vs y and obtained a plot of points, now I'm trying to fit a curve to my data using a nonlinear polynomial of order 4, the coeficiants are unknown.
I aim to obtain the regression coefficient as well.
Any idea how it is possible to do this? what are the suitable matlab functions to plot the fitting curve and to obtain the regression coeficient?
I already tried polyfit, but is it correct? if yes then how to proceed?

Answers (3)

KSSV on 19 Nov 2018
Edited: KSSV on 19 Nov 2018
Yes polyfit is the function you need.
x = linspace(0,4*pi,50);
y = sin(x);
% Use polyfit to fit a 4th-degree polynomial to the points.
p = polyfit(x,y,7);
% Evaluate the polynomial on a finer grid and plot the results.
x1 = linspace(0,4*pi);
y1 = polyval(p,x1);
hold on
hold off
In the above p has your coefficients. YOu can use poly2sym to see the polynomial obtained.
Sarah on 20 Nov 2018
so i tried this as below, but the resulting fitting does not apear same as it is when done on excel.
x =[6 values input by the user ]
y = [6 values calculated ]
so x and y are the same size
p = polyfit(x, y, 4);
val = polyval(p, x);
plot(x, y, 'o');
hold on;
plot(x, val);
hold off

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madhan ravi
madhan ravi on 19 Nov 2018
Read interp1 and use appropriate method you want
x = linspace(0,4*pi,50);
y = sin(x);
xx = linspace(x(1),x(end),1000);
yy = interp1(x,y,xx,'spline')
Sarah on 19 Nov 2018
then how can i get the regression coeficient if I am sing the interp1 method?

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Luna on 19 Nov 2018
Edited: Luna on 19 Nov 2018
Hello Sarah,
you can use polyfit. It uses least squares, here is the link you can read about it:

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