Hi Ptit,
>> I would like to fit data with the following formula :
>> y=V*(1+alpha*(x-25))
>> where y and x are my data, V is a constant and alpha is the slope
I'm
>> looking for.
Priorities first: lm() or ordinary least-square regression is a basically a
method for finding the best-fitting straight line through a set of points
(assuming that x is measured without error). So lm() determines the slope;
it's usually what you are trying to estimate.
Perhaps you are after abline:
?abline
You can feed this coefficients (i.e. your intercept and slope), and then
plot over an existing scatterplot.
##
plot(x,y)
abline(a=intercept, b=slope) ## or: abline(coef=c(intercept, slope))
HTH, Mark.
Ptit_Bleu wrote:>
> Hello,
>
> I would like to fit data with the following formula :
> y=V*(1+alpha*(x-25))
> where y and x are my data, V is a constant and alpha is the slope I'm
> looking for.
>
> How to translate this into R-language ?
> At the moment, I only know : lm(y ~ x)
>
> Sorry for such a basic question. I thought I could find the solution in a
> post but I have to confess that, up to know, I'm not able to understand
> the posts I read concerning lm (the level of the questions are too high
> for me and my english quite poor as well).
>
> Have a nice evening,
> Ptit Bleu.
>
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