>> 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 OK, sorry you are correct: one would need also to calculate residuals as (y - ymodel)^2*t instead of (y - ymodel)^2 in the case of nls. This effects also nlrq, although in a somewhat reduced manner. Best, Philippe Grosjean ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
