On Wed, May 2, 2012 at 3:32 PM, Michal Figurski <figur...@mail.med.upenn.edu> wrote: > Dear R-Helpers, > > I'm working with immunoassay data and 5PL logistic model. I wanted to > experiment with different forms of weighting and parameter selection, which > is not possible in instrument software, so I turned to R. > > I am using R 2.14.2 under Win7 64bit, and the 'nls' library to fit the model > - I started with the same model and weighting type (1/y) as in the > instrument to see if I'll get similar results. However, in some instances I > don't get any results - just errors. > > Here is an example calibration data, representative of my experiment. > Instrument soft had no problem fitting it: > x <- structure(list(SPL = structure(c(1L, 1L, 2L, 2L, 3L, 3L, 4L, > 4L, 5L, 5L, 6L, 6L, 7L, 7L), .Label = c("St1", "St2", "St3", > "St4", "St5", "St6", "St7"), class = "factor"), MFI = c(10755.5, > 9839, 5142.5, 4857, 1510.5, 1505, 502.5, 451, 215, 195.5, 58, > 57, 15, 15), nom = c(206, 206, 125, 125, 68, 68, 38, 38, 24, > 24, 13, 13, 6.5, 6.5), weights = c(0.0013946353028683, 0.00152454517735542, > 0.00291686922702965, 0.00308832612723904, 0.0099304865938431, > 0.00996677740863787, 0.0298507462686567, 0.0332594235033259, > 0.0697674418604651, 0.0767263427109974, 0.258620689655172, > 0.263157894736842, > 1, 1)), .Names = c("SPL", "MFI", "nom", "weights"), row.names = c(NA, > -14L), class = "data.frame") > > And here is the nls fit: > fit <- nls(MFI~a + b/((1+(nom/c)^d)^f), data=x, weights=x$weights, > start=c(a=100, b=10000, c=100, d=-1, f=1)) >
This looks quite linear to me: fo <- log(MFI) ~ log(nom) plot(fo, x) abline(lm(fo, x)) Try using that as the basis for an alternate model. -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.