How to force the intercept of a regression line to zero?

Hi; How to set the intercept of a regression line,, resulted from fitlm, to zero?

 clc
X = 1:10
y = [1, 2, 2.9, 4, 5.1, 6, 7, 7.8, 8.6, 9.5]
dlm = fitlm(X,y)

Thank you, in advance, for your help.

[Brendan Hamm]

I would highly suggest learning the Wilkinson notation, as this allows you to fit models and specify the form of the equation you would like to fit.

Answer 1

[Brendan Hamm]

There are 2 main ways you can do this:

dlm = fitlm(X,y,'Intercept',false);

or using Wilkinson notation:

dlm = fitlm(X,y,'y~x1-1');

I would highly suggest learning the Wilkinson notation, as this allows you to fit models and specify the form of the equation you would like to fit.

[DEWDROP]

could you please tell me what is the difference between mdl=fitlm and dlm=fitlm while fitting the regression line?

[John D'Errico]

@DEWDROP

You can name an output variable to be anything you want. There is NO relevance.

Answer 2

[George Tzintzarov]

I would use the 'fittype' function:

ft1 = fittype({'x'}) %This creates a linear 'fittype' variable that is of the form f(a,x)=ax.
ft2 = fittype({'x','1'}) %This creates a linear 'fittype' variable that is of the form f(a,x)=ax+b.

Then fit and evaluate to values you want: (Note that in the fit function x and y must be column vectors)

x = [1 2 3 4]; y = [2 3 4 5]; 
p1 = fit(x',y',ft1); %This creates a 'cfit' variable p that is your fitted function
p2 = fit(x',y',ft2); %This creates a 'cfit' variable p that is your fitted function
x_fit = linspace(0,6,10); %x-values to evaluate
y1_fitted = feval(p1, x_fit); %y-values for the evaluated x-values
y2_fitted = feval(p2, x_fit); %y-values for the evaluated x-values

Here is what you should get:

plot(x,y,'ro'); hold on;
plot(x_fit,y1_fitted,'b-')
plot(x_fit,y2_fitted,'b--')
legend({'Raw Data','Fitted with y-int','Fitted through (0,0)'})

[Vladimir Jara]

any solution withoug additional toolboxs?