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

[Martin Maechler]

>>>>> PIKAL Petr <petr.pikal at precheza.cz>
>>>>>     on Fri, 20 Oct 2017 13:35:01 +0000 writes:

    > Thank you Martin.
    > If I understand correctly, OP could do

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

(which is really a different model with one parameter more, and
 given the relatively small sample size per group, it may not be
 the best idea)

    > 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.
    > plot(augPred(wheat.list))

    > Am I correct?

Yes, indeed, Petr,  I forgot to mention that obvious workaround.

(Interestingly, he could also _subtract_ a small positive value
 which is less intuitive, but work too given the code I showed.)

Martin



    > Cheers
    > Petr

    >> -----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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