You want the offset function in the formula:

lm( A ~ B + I(B^2) + offset(C), data=Dataset)

This will force the coefficient on C to be 1, if you wanted a coefficient
of another value then just do the multiplication yourself, e.g. offset( 2 *
C ) for a slope of 2.

Also you can use poly(B,2) to fit a linear and quadratic terms on B.


On Thu, Oct 17, 2013 at 3:45 AM, Robert U <tacsunday@yahoo.fr> wrote:

> Dear all,
>
> I have been trying to  find a simple solution to my problem without
> success, though i have a feeling a simple syntaxe detail coul make the job.
>
> I am doing a polynomial linear regression with 2 independent variables
> such as :
>
> lm(A ~ B + I(B^2) + I(lB^3) + C, data=Dataset))
>
> R return me a coefficient per independent variable, and I  would need the
> coefficient of the C parameter to equal 1.
>
>
> I've been loonking at "parameter constraints" on the  internet but it's
> always much more complicated that just "removing" the fit of a coefficient
> (or setting it to 1).
>
>
> I know many package allows to "not fit" an intercept with a "-1" parameter
> in the syntaxe, does that exists for independent variables ?
>
> Regards,
>         [[alternative HTML version deleted]]
>
>
> ______________________________________________
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
>
>


-- 
Gregory (Greg) L. Snow Ph.D.
538280@gmail.com

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