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

[Juan Pablo Carbajal]

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
>
>
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> address@hidden
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>

Krishnaprasad

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
example

X = randn(10,5);
y = X*linspace(-1,1,5).' + 0.01*randn(10,1);
B = regress (y, X);
plot(y,'.;data;',X*B,'o;train;')
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
results.

Hope this helps.