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

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).

Answer 1

[the cyclist]

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);

[Lucas Barboza]

Yes, thanks.

In my case, with 4 predictors, I need to use:

X = [ones(size(x1)) x1 x2 x3 x4]; .