[R] nls, nlrq, and box-cox transformation
kjetil@entelnet.bo
kjetil at entelnet.bo
Fri Nov 21 01:12:35 CET 2003
On 20 Nov 2003 at 15:24, Philippe Grosjean wrote:
> >Dear r-help members
> >I posted this message already yesterday, but don't know whether it
> >reached you since I joined the group only yesterday. I would like to
> >estimate the boxcox transformed model
> > (y^t - 1)/t ~ b0 + b1 * x.
> >Unfortunately, R returns with an error message when I try to
> >perform this with the call
> >nls( I((y^t - 1)/t) ~ I(b0 + b1*x),
> > start = c(t=1,b0=0,b1=0), data = mydataframe)
>
> >The error message is: Object "t" not found
>
> >Apparently R seems not to accept parameters on the left hand
> >side of a regression model. I know that my do-it-yourself
> >strategy is not necessary, since the package box-cox is
> >available. Unfortunately, I want the use the box-cox
> >transformation in a quantile regression, i.e. I have to replace
> >nls by nlrq in the call above.
>
> >Any suggestions?
>
> >Thanks and best regards,
> > Johannes Ludsteck
>
> You suggest the solution yourself: transform the equation to have all
> parameters at the right, thus:
>
> y ~ ((b0 + b1 * x) * t + 1) ^ 1/t
>
Bit this is still not correct, since the transformation changes
the scale of the variance, and lesat squares will not be correct.
There is needed a factor (the jacobian) to compensate for this,
Kjetil Halvorsen
> (double check if this is correct)
>
> Best,
>
> Philippe Grosjean
>
> ...........]<(({?<...............<?}))><..............................
> .
> ) ) ) ) )
> ( ( ( ( ( Dr. Philippe Grosjean
> ) ) ) ) )
> ( ( ( ( ( Numerical Ecology Laboratory
> ) ) ) ) ) Mons-Hainaut University
> ( ( ( ( ( 8, Av. du Champ de Mars, 7000 Mons
> ) ) ) ) ) Belgium
> ( ( ( ( (
> ) ) ) ) ) e-mail: phgrosjean at sciviews.org
> ( ( ( ( ( SciViews project coordinator (http://www.sciviews.org)
> ) ) ) ) )
> ......................................................................
> .
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
More information about the R-help
mailing list