[R] Error messages using nonlinear regression function (nls)

PIKAL Petr petr.pikal at precheza.cz
Fri Oct 20 15:35:01 CEST 2017

Thank you Martin.

If I understand correctly, OP could do

wheat.list <- nlsList(Prop ~ SSfpl(end, A, B, xmid, scal), data=wlg)

or add some small value to all zeroes

wlg$prop < -wlg$Prop+1e-7
wheat.list <- nlsList(prop ~ SSlogis(end,Asym, xmid, scal), data=wlg)

which gives fairly reasonable results.

Am I correct?


> -----Original Message-----
> From: Martin Maechler [mailto:maechler at stat.math.ethz.ch]
> Sent: Friday, October 20, 2017 1:04 PM
> To: PIKAL Petr <petr.pikal at precheza.cz>
> Cc: Wall, Wade A ERDC-RDE-CERL-IL CIV <Wade.A.Wall at erdc.dren.mil>; r-
> help at r-project.org
> Subject: Re: [R] Error messages using nonlinear regression function (nls)
> >>>>> PIKAL Petr <petr.pikal at precheza.cz>
> >>>>>     on Fri, 20 Oct 2017 06:33:36 +0000 writes:
>     > Hi
>     > Keep your messages in the list, you increase your chance to get some
> answer.
>     > I changed your data to groupedData object (see below), but I did not find
> any problem in it.
>     > plot(wlg)
>     > gives reasonable picture and I am not such expert to see any problem with
> data. Seems to me, that something has to be wrong with nlsList function.
>     >> wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid, scal), data=wlg)
>     > Warning message:
>     > 6 times caught the same error in lm.fit(x, y, offset = offset, singular.ok =
> singular.ok, ...): NA/NaN/Inf in 'x'
>     > produces empty list. So maybe others could find some problem.
>     > Cheers
>     > Petr
> Thank you, Petr,  for the reproducible example.
> This indeed can be traced back to a bug in SSlogis() that has been there since
> Doug Bates added the 'nls' package on Martin's day 1999 (==> before R version
> 1.0.0 !) to R (svn rev 6455).
> It's this part which does contain a thinko (by whomever, only Doug may be able
> to remember/recall, but I guess it would have been José Pinheiro, then the grad
> student doing the nitty gritty), I have added 2 '----------' below to make the 2
> important lines stand out :
>    z <- xy[["y"]]
>  ---------------------------------------------------------------------
>    if (min(z) <= 0) { z <- z - 1.05 * min(z) } # avoid zeroes
>    z <- z/(1.05 * max(z))             # scale to within unit height
>  ---------------------------------------------------------------------
>    xy[["z"]] <- log(z/(1 - z))                # logit transformation
>    aux <- coef(lm(x ~ z, xy))
> the first of the 2 lines,  commented   "avoid zeroes"
> is obviously *not* avoiding zeroes in the case min(z) == 0 , and even though the
> 2 lines  should rescale an interval  [0, M] to [eps, 1 - eps] they don't in this case.
> Consequently, the next line  log(z/(1 - z))  transforms the 0s into -Inf  and these
> lead to the warning (or error in nls())
>   " NA/NaN/Inf in 'x' "
> One could fix this up by  replacing  min(z)  by  min(z, -1e-7) which may be best
> for pure back compatibility, but I really don't like it either :
> The famous  logit - transform   log( z / (1-z))
> is really anti-symmetric around z = 1/2 , in particular should treat 0 and 1
> "symmetrically" and I find it ugly that the previous fixup (our two ominous
> lines) is not at all symmetric wrt 1/2, notably the 2nd transformation is made
> unconditionally but the first one not.
> Fortunately, the same source file, <R>/src/library/stats/R/zzzModels.R
> also defines  the SSfpl()  == 4-parameter logistic model
> and there, the 'init' function needs to do the same scaling to (0, 1)  and does it
> much nicer, indeed (anti)symmetrically.
> I'm looking into using that in SSlogis() as well, fixing this bug.
> Martin Maechler
> ETH Zurich and R Core Team

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