How to find the equation of a graph after getting Xdata and Ydata ?

x = [0 1 2 3 4 5 6 7 8 9 10];
y = [4 3 4 7 12 19 28 39 52 67 84];
% How to find the function y = F(x) ??
% because I need for example to know
% if x = 1.5
% y = ??
% the solution should be something regarding regression.

 Akzeptierte Antwort

Azzi Abdelmalek
Azzi Abdelmalek am 7 Aug. 2015
Bearbeitet: Azzi Abdelmalek am 7 Aug. 2015
You can find yi by interpolation
x = [0 1 2 3 4 5 6 7 8 9 10];
y = [4 3 4 7 12 19 28 39 52 67 84];
xi= 1.5
yi=interp1(x,y,xi)

Weitere Antworten (2)

The easiest way would be to use the polynomial fitting functions. For this you need to know what order polynomial to fit, so visualize the data:
plot(x,y)
The data you gave looks quadratic, so let's find the coefficients for a second order polynomial:
coeff = polyfit(x,y,2);
Now evaluate the polynomial at a new value of x:
xNew = 1.5;
yNew = polyval(coeff,xNew);
plot(xNew,yNew,'r*');

5 Kommentare

For more complex linear models you can take a look at fitlm in the Statistics and Machine Learning Toolbox.
Yes this solution works too. But the first one is more simple. Thinks.
If you want to assume the data you had was from a one dimensional polynomial, then this works fine (as interp1 is doing a 1 dimensional linear interpolation). On the other hand if you want the requirement that, "the solution should be something regarding regression", then polyfit or fitlm would be the appropriate choice.
Thanks for the advice.
Yes, Finally I used Polyfit

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one of the infinite number of solutions is:
x = [0 1 2 3 4 5 6 7 8 9 10];
y = [4 3 4 7 12 19 28 39 52 67 84];
pp = polyfit(x, y, length(x)-1);
y1_5 = polyval(pp, 1.5)
Another of the infinite solutions is:
x = [0 1 2 3 4 5 6 7 8 9 10];
y = [4 3 4 7 12 19 28 39 52 67 84];
y1_5 = 19;
It is not mathematically possible to distinguish between these two solutions as to which one is "more correct".

2 Kommentare

It is exactelly what I used, because I didn t know the order of the polynom.

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