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Re: Model object as output for linear regression in Octave 3.8

From: Juan Pablo Carbajal
Subject: Re: Model object as output for linear regression in Octave 3.8
Date: Mon, 22 Sep 2014 14:50:40 +0200

On Mon, Sep 22, 2014 at 1:40 PM, Narayanan, Krishnaprasad
<address@hidden> wrote:
> Hallo all,
> I am using Octave 3.8.0 to build a linear model that has several input
> features and one output feature. I will be using this model in order to
> predict the output for the given set of input features. When I searched on
> the web for statistical packages, I found the following functions: polyfit
> and regress. But none of these functions returns me a model object which I
> can use it for prediction.
> Can I kindly know from the forum is there a function in octave that returns
> me a model object for linear regression?
> Regards,
> Krishnaprasad
> _______________________________________________
> Help-octave mailing list
> address@hidden


If you want to use linear regression you do not need polyfit. The
function regress indeed returns a model you can use, here a minimalist

X = randn(10,5);
y = X*linspace(-1,1,5).' + 0.01*randn(10,1);
B = regress (y, X);
X_new = randn(100,5);
y_predict = X_new*B

Just make sure you read the help of regress to understand its outputs
and also check your theory on linear regression for more robust

Hope this helps.

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