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 Multiple Linear Regression with conditions
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JinsungKim

1 Posts

Posted - 05/31/2012 :  02:53:23 AM  Show Profile  Edit Topic  Reply with Quote  View user's IP address  Delete Topic
Origin Ver. and Service Release (Select Help-->About Origin): Origin 8 SR 4.0
Operating System: MS Windows 7

Origin Ver. and Service Release (Select Help-->About Origin): 8.0 SR4
Operating System: MS Windows 7

Hi guys,

I am now dealing with multiple linear regression.
Though I can manage how to run mulutiple linear regression in Origin, I wonder whether there are any optional functions which work to boundary conditions among coefficients of independent variables.

I.e., consider multiple linear regression below.

Y = a + bx + cz + e where Y is dependent variable, x and z are independent variables, a is constant, e is random error term, b and c are coefficient of interest.

Normally, Origin greatly compute best value of b and c but I would like to add one more condition to about b and c, such as b+c = 1.

Therefore, total algebraic system would be as following.

Y = a + bx + cz +e, b + c = 1.

Is Origin possible to find b and c with multiple linear regression method under certain condition (b+c=1)? Is Origin possible to lay certain condition in multiple linear regression dialogue window?

Thanks to your help!

Jinsung

Hideo Fujii

USA
1582 Posts

Posted - 05/31/2012 :  12:03:52 PM  Show Profile  Edit Reply  Reply with Quote  View user's IP address  Delete Reply
Hi Jinsung,

Though the multiple regression tool doesn't have linear constraint option, instead, you can
define a user-defined fitting function with multiple independent variables; and you can use
the non-linear fitting tool, NLFit. In NLFit, you can set linear constraints like yours.
As for the way to set the linear constraints, you can refer to the following tutorial page:

http://wiki.originlab.com/~originla/howto/index.php?title=Tutorial:Fit_Curve_Through_Certain_Points#Use_Linear_Constraint

Hope this helps.

--Hideo Fujii
OriginLab

P.S. There is a video tutorial, "Origin: Using Linear Constraints When Fitting":
http://www.youtube.com/watch?v=Fh7broKA8AU

Edited by - Hideo Fujii on 05/31/2012 4:12:25 PM
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