[RsR] error/warning messages with lmrob()

[Stahel Werner A.]

Sorry, Martin and Emily, for this stupid mistake.

Just to make things very concrete, you might use


lmrob( y~year, method="M", init=lmrob.lar, psi="lqq")


Please let us know if there are still warnings with this version.


Best regards. Werner


Werner Stahel
M +41 79 784 9330 | P +41 44 364 6424
________________________________
Von: Martin Maechler <maechler using stat.math.ethz.ch>
Gesendet: Montag, 26. August 2019 10:00:01
An: Stahel Werner A.
Cc: Emily Klein; r-sig-robust using r-project.org
Betreff: Re: [RsR] error/warning messages with lmrob()

>>>>> Stahel Werner A
>>>>>     on Sat, 24 Aug 2019 21:04:04 +0000 writes:

    > Dear Emily

    >  A short answer also to your questions about
    > non-convergence of lmrob.  You are using it to
    > characterize the trend in many time series.  I assume that
    > the problems are caused by the series being short.  I
    > would be interested in getting some of those that cause problems.

Indeed, me too. (we mean getting the datasets, e.g., sending us
         the file  'lmrob-problm.rds'  after

   saveRDS(<your-data-frame>, file = "lmrob-problm.rds")

)

    > For a simple regression, you may fall back on good old
    > rlm(...)  In the meantime, I will again try to convince
    > the maintainers of lmrob to introduce the possibility of
    > providing initial values that allow for avoiding the
    > initial S step -- since this step causes the problems.

Well, 'init' has been an argument of lmrob() "forever", and has
quite a nice paragraph on the help page of lmrob (search for
"initial estimator") *and* another paragraph in the 'Examples'
of the help page, online versions of which are nowadays easily found by googling
'lmrob robustbase'), notably these two:
- https://www.rdocumentation.org/packages/robustbase/versions/0.93-5/topics/lmrob
- https://rdrr.io/cran/robustbase/man/lmrob.html

[I really would not go back to use rlm().]

Martin


    > Best regards. Werner

    > Werner Stahel M +41 79 784 9330 | P +41 44 364 6424
    > ________________________________
    >> Von: R-SIG-Robust <r-sig-robust-bounces using r-project.org> im
    >> Auftrag von Emily Klein <emily.klein04 using gmail.com>
    >> Gesendet: Montag, 15. Juli 2019 21:45:00 An:
    >> r-sig-robust using r-project.org Betreff: [RsR] error/warning
    >> messages with lmrob()
    >>
    >> Dear all,
    >>
    >> I am running lmrob() under the robustbase package, and I
    >> have a few error/warning messages I would greatly
    >> appreciate help with - I am unfamiliar with robust linear
    >> models, so my apologies in advance if the answers here
    >> are obvious. In addition, any discussion will help me get
    >> a handle on what we're doing, which always helps.
    >>
    >> (1) I get the repeated error seemingly on random species
    >> when running a loop of lmrob() over all our ecological
    >> time series (different ones almost every time):
    >>
    >> Error in eigen(ret, symmetric = TRUE) : infinite or
    >> missing values in 'x'
    >>
    >> I have checked my data many times, and if I just
    >> repeatedly run lmrob() it eventually works. Any idea what
    >> this error is in reference to? Could it be because I am
    >> using a previous version of R (3.4.1)?
    >>
    >> (2) I have several two error messages that come up with
    >> some time series; I have some idea their meaning, but
    >> again, as a newbie with RLMS, I am wondering if those
    >> time series that garner these warnings should be excluded
    >> from our meta-analysis. Also, any additional insight on
    >> the process or something I might be missing greatly
    >> welcomed!
    >>
    >> Warning in lmrob.S(x, y, control = control) :
    >> find_scale() did not converge in 'maxit.scale' (= 200)
    >> iterations with tol=1e-10, last rel.diff=0
    >>
    >> Warning in lmrob.fit(x, y, control, init = init) : M-step
    >> did NOT converge. Returning unconverged SM-estimate
    >>
    >> Warning in lmrob.S(x, y, control = control) : S-estimated
    >> scale == 0: Probably exact fit; check your data
    >>
    >> Thank you very much in advance,
    >>
    >> Emily
    >>
    >>
    >> --
    >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    >> Emily S. Klein, Senior Postdoctoral Associate (she / her
    >> / hers) The Frederick S. Pardee Center for the Study of
    >> the Longer-Range Future | Boston University *Co-Chair*,
    >> ICES Working Group on the History of Fish & Fisheries
    >> (WGHIST) esklein04 using gmail.com
    >>
    >> http://www.bu.edu/pardee/
    >> http://www.ices.dk/community/groups/Pages/WGHIST.aspx

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