On Thu, 20 Nov 2003, 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 > > (double check if this is correct)
But for nls that changes the fitting criterion from least-squares to something completely different. For the original problem, this is not the correct Box-Cox transformation, as the normalizer has been omitted. I am unaware of `package box-cox' (and that is not a valid package name AFAIK), but function boxcox in MASS computes the correct likelihood. Now nlrq uses a different criterion and Philippe's suggestion may work there. I can't tell quickly: the help page does not say what the criterion is. But if those are the same, then I suspect the criterion is uninteresting as a way to choose t, since two of the three aims of Box-Cox are to stabilize the distribution of lhs - rhs. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
