Do what Excel does in curve fitting in Matlab

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Samuel
Samuel 2012-4-25
Hello all, thanks in advance for your help!
I know that Matlab is loaded with all sorts of curve fitting software that can utilize a whole bunch of different functions in order to give the best fitting possible.
However, I just have some simple data that I wish to fit a linear standard line to- make the line go through 0 and show the r squared value, and show the equation. I also wish to show this for my plot that has more than one "function" plotted (this is because I noticed that using the tools method in the plot interface only allows one curve to be fit, and doesn't show the rsquared value).
If anybody can list out what I can add to my code to implement these simple aspects, that will be great.
Thanks again. sam

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回答（3 个）

Teja Muppirala
Teja Muppirala 2012-4-25
Wayne gives a good way to do it, but in the latest version of the Statistics Toolbox, there is some great functionality that makes this stuff even easier::
x = 1:100;
y = 2*x+ 4*randn(size(x));
F = LinearModel.fit(x,y,'linear','intercept',false)
plot(F)
F.Rsquared
See "help LinearModel" for more information
  2 个评论
Samuel
Samuel 2012-4-25
Thanks for the help. I actually have the statistics toolbox when i check the versions, but strangely when I adapt and run the code as you wrote, it gives me an error saying
Undefined variable "LinearModel" or class "LinearModel.fit".
and typing help LinearModel gives an error
LinearModel not found.
i have matlab r2011b for mac and windows. what might be the problem?
thanks!
Teja Muppirala
Teja Muppirala 2012-4-26
Hello Samuel,
The LinearModel class was just introduced recently in the R2012a release.
You may have to use the other methods mentioned instead.

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Wayne King
Wayne King 2012-4-25
Are you really sure you want to force the line to go through zero?
Do you have the Statistics Toolbox? If so, use regress()
x = 1:100;
y = 2*x+ 4*randn(size(x));
X = ones(length(y),2);
X(:,2) = x';
[beta,bint,r,rint,stats] = regress(y',X);
Fitted line is yhat = beta(1)+beta(2)*x. Rsquared is
stats(1)
plot(x,y,'k*'); hold on;
yhat = beta(1)+beta(2)*x;
plot(x,yhat,'r','linewidth',2);
  1 个评论
Samuel
Samuel 2012-4-25
Hello Wayne, thanks for the help!
I actually tried implementing your method, but when I execute it, I get an error that states matrix dimensions must agree. It seems that the X matrix should be only 1 column in order for the regress function to work? Any clarification will be helpful! Thanks.

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Daniel Shub
Daniel Shub 2012-4-25
While it doesn't do everything you want I would suggest looking at the source for lsline
type lsline
It takes care of plotting multiple lines. It makes use of polyfit
doc polyfit
which provides the r^2 value you want
Adding the equation for a line that goes through the intercept seems a bit odd to me ...

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