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How to use the regress function for more than 2 predictors?

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I need to make a multiple linear regression with 4 predictor, like x1, x2, x3 and x4. So, i discovered the function regress.
In the doc, there is the example bellow:
load carsmall
x1 = Weight;
x2 = Horsepower; % Contains NaN data
y = MPG;
X = [ones(size(x1)) x1 x2 x1.*x2];
b = regress(y,X) % Removes NaN data
But, in my case, i have x1, x2, x3 and x4. I don´t know how to use correct for this case, and i don't know how create the array X (showed in the doc of Matlab).

Accepted Answer

the cyclist
the cyclist on 8 Aug 2017
Does this example using 3 variables help?
% Load the data
load carsmall
% Redefine names, to look more like your problem
% Explanatory variables
x1 = Weight;
x2 = Horsepower;
x3 = Displacement;
% Response variable
y = MPG;
% Put all the explanatory variables (including a constant term) into one matrix
X = [ones(size(x1)) x1 x2 x3];
% Estimate the parameters
b = regress(y,X);

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