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Hi,

I am looking for a matlab function that is working similar to polyfit, but where I can use two different input function but instead of having just one linear term, I need two. At the moment the regression looks as follows:

y=b0+b1*x+error

and the code to compute R^2 is the following:

x= changePriceWithoutNaN;

y=changeFWithoutNaN;

p = polyfit(x,y,1);

f = polyval(p,x);

plot(x,y,'o',x,f,'-')

yfit = polyval(p,x);

yfit = p(1) * x + p(2);

yresid = y - yfit;

SSresid = sum(yresid.^2);

SStotal = (length(y)-1) * var(y);

rsq_full = 1 - SSresid/SStotal

Instead of having just one linear term, the term I am looking for is the following:

y=b0+b1*x+b2*z+error

Is there anybody how knows a function that is solving a least squared optimazation in the way to coe above does? Importat is that I do not look for a quadratic solution and therefore from what I can see polyfit(x,y,2) is not an option

Shashank Prasanna
on 1 May 2013

Edited: Shashank Prasanna
on 1 May 2013

Locks, it seems like you are interested in multiple linear regression. If you have the stats toolbox you can use the REGRESS function to do that. If you don't then you can use a simple '\' as follows:

x = dataT(:,2);

%is the implied volatility

y = dataT(:,10);

z = dataT(:,15);

p = [x z ones(length(dataT))]\y

p will have the 3 coeff you desire. We are essentially solving a linear system in a least square sense.

Shashank Prasanna
on 3 May 2013

It is indeed in the documentation, please go through it closely. This will help you find things later yourself :

and the answer is already in your code, I encourage you to take a closer look.

Hint:

tstat = mdl.Coefficients.tStat

Once again, please go through the documentation, fundamentally, all properties can be accessed with the '.' dot notation from your model.

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Matt J
on 29 Apr 2013

There are several multi-dimensional polynomial fitters on the FEX, e.g.,

Matt J
on 1 May 2013

Matt J
on 2 May 2013

As said, the regression must stay linear, I do not want any quadratic components

And as I keep telling you, if you want to have only linear terms, then tell that to polyfitn:

p = polyfitn([x,y],z,1);

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