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

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Ali Y.
Ali Y. 2015-7-16
评论： John D'Errico 2022-8-12
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.
  1 个评论
Brendan Hamm
Brendan Hamm 2015-7-16
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.

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采纳的回答

Brendan Hamm
Brendan Hamm 2015-7-16
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.
  2 个评论
DEWDROP
DEWDROP 2020-5-10
could you please tell me what is the difference between mdl=fitlm and dlm=fitlm while fitting the regression line?
John D'Errico
John D'Errico 2022-8-12
@DEWDROP
You can name an output variable to be anything you want. There is NO relevance.

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更多回答（1 个）

George Tzintzarov
George Tzintzarov 2018-10-6
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)'})

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