[R] ANCOVA error again
Birgit Lemcke
birgit.lemcke at systbot.uzh.ch
Mon Apr 21 17:21:44 CEST 2008
Hello Gavin,
thanks for you answer.
If I use it without " with" I get back the same error.
The "with" thing was only to try out for functions that do not
contain a data-argument. I still try to learn and therefor I
sometimes just try.
It is understood that I am on the way to simplify the model once I
have it for the hole slot.
I don`t wanna predict the gender.
I would like to know which of my variables are the strongest to
divide all into the already existing groups: male and female.
In the case that all my variables would be continuous, I could have
probably used a discriminant function analysis, but most of the
variables are categorical.
My plan is to delete in each case, one of the interacting variables
and then compare the models with the left over variables using a
ChiSquare test.
But I am always open for suggestions, because I am still not very
good in statistics.
Presently I still have the same error message and don`t know how to
fix this.
Greets
B.
Am 21.04.2008 um 16:52 schrieb Gavin Simpson:
> On Mon, 2008-04-21 at 15:43 +0200, Birgit Lemcke wrote:
>> Hello R users!
>>
>> I got again an error message.
>
> Something here is causing compiled code to segfault ("crash"). I don't
> know what the problem is here exactly --- I'll let those much more
> acquainted with R look into that --- but you seem to be using R's
> model
> formulae in a non-standard way.
>
> You don't need with() wrapping your call to glm(), just include a data
> frame as the data argument:
>
> ModelFemMal85 <- glm(Sex ~ .^2, data = FemMal85_Sex,
> na.action = na.exclude, family = binomial)
>
> Will do what you appear to have attempted below (all main effects plus
> first order interactions). This is a simpler call so see if this will
> work in R without causing the segfault.
>
> However, I would consider what on earth you are going to do with
> such a
> huge number of coefficients in the model --- over 3500 if I
> interpretted
> your formula correctly and assuming that the variables are all
> continuous. You do have many, many more than 3500 observations?
>
> If you are trying to predict the sex of individuals, why not try
> some of
> the classification techniques available in R? A simple technique would
> be a classification tree (packages rpart and party for example). These
> will help with feature selection and do include interactions,
> though not
> in exactly the same way you have done so here. Bagging, boosting or
> randomForests could be used to improve predictions (or make them more
> stable). Check out the Machine Learning and Environmetrics Task Views
> for additional info and pointers to relevant R packages/functions.
>
> My two pennies worth,
>
> G
>
>>
>> I used this code:
>>
>> with (FemMal85_Sex, {
>> ModelFemMal85<- glm
>> (Sex~outLatTep_like_other*outLatTep_like_conduplicate*outLatTep_keele
>> d_w
>> inged*spathellae_conspicuous*spathellae_inconspicuous_absent
>>
>> *InfSpath_persistence*InfSpath_caducuous*bractsSpacing_lax*bractsSpac
>> ing
>> _imbricate*InfType_sparsely_paniculate*InfType_racemose*InfType_panic
>> ula
>> te*InfType_globose*bracApexShape_truncate
>> *bracApexShape_rounded
>> *bracApexShape_obtuse
>> *bracApexShape_acute
>> *bracApexShape_acuminate
>> *bracApexShape_apiculate
>> *bracApexShape_aciculate
>> *BracUpperMarg_like_rest*BracUpperMarg_memebranous*BracUpperMarg_hone
>> yco
>> mbed_cells*InfSpathText_coriaceous*InfSpathText_hyaline*InfSpathText_
>> cha
>> rtaceous*InfSpathText_cartilaginous*InfSpathText_membranous*spikShape
>> Sid
>> e_linear*spikShapeSide_oblong*spikShapeSide_square*spikShapeSide_elli
>> pti
>> cal*spikShapeSide_ovate*spikShapeSide_obovate*spikShapeSide_obtriangu
>> lar
>> *spikShapeSide_orbicular*spikShapeSide_undifferentiated*SpikApexShape
>> _tr
>> uncate*SpikApexShape_rounded*SpikApexShape_obtuse*SpikApexShape_acute
>> *Sp
>> ikApexShape_undifferentiated*BracShape_linear*BracShape_oblong*BracSh
>> ape
>> _square*BracShape_elliptical*BracShape_ovate*BracShape_obovate*BracSh
>> ape
>> _orbicular*BracText_bony*BracText_coriaceous*BracText_hyline*BracText
>> _ch
>> artaceous*BracText_cartilaginous
>> *BracText_membranous
>> *BracText_centrChartaceousMargMembranous
>> *TepText_bony*TepText_coriaceous*TepText_chartaceous
>> *TepText_cartilaginous
>> *TepText_membranous*InfLengthMin*InfLengthMax*InfWidthMin*InfWidthMax
>> *Sp
>> athellaeLengthMin*SpathellaeLengthMax*SpikLengthMin*SpikLengthMax*Flo
>> wNu
>> mbSpikMin*FlowNumbSpikMax*BracLengthMin*BracLengthMax*FlowLengthMin*F
>> low
>> LengthMax*InfSpathLengthToSpikMin*InfSpathLengthToSpikMax*TepInOutMin
>> *Te
>> pInOutMax*BracLengthtoFlowMin*BracLengthtoFlowMax*BracMargMin*BracMar
>> gMa
>> x*BracAwnToBodyMin*BracAwnToBodyMax,
>> na.action=na.exclude,family=binomial)})
>>
>> and got this error message:
>>
>> *** caught segfault ***
>> address 0xbf7fffb0, cause 'memory not mapped'
>>
>> Traceback:
>> 1: terms.formula(formula, data = data)
>> 2: terms(formula, data = data)
>> 3: model.frame.default(formula = Sex ~ outLatTep_like_other *
>> outLatTep_like_conduplicate *........... * BracAwnToBodyMax,
>> drop.unused.levels = TRUE)
>> 4: model.frame(formula = Sex ~ outLatTep_like_other *
>> outLatTep_like_conduplicate *........... * BracAwnToBodyMax,
>> drop.unused.levels = TRUE)
>> 5: eval(expr, envir, enclos)
>> 6: eval(mf, parent.frame())
>> 7: glm(Sex ~ outLatTep_like_other * outLatTep_like_conduplicate
>> *............* BracAwnToBodyMax, family = binomial)
>> 8: eval.with.vis(expr, envir, enclos)
>> 9: eval.with.vis(ei, envir)
>> 10: source("/Users/birgitlemcke/Job/Doktorarbeit/R/Protokolle_Codes/
>> Protokoll21.04.08.R")
>>
>> Possible actions:
>> 1: abort (with core dump, if enabled)
>> 2: normal R exit
>> 3: exit R without saving workspace
>> 4: exit R saving workspace
>> Selection:
>>
>>
>>
>> ........... I deleted here some of the 85 variables
>>
>> What does this message mean?
>>
>> Thanks a lot in advance.
>>
>> B.
>>
>>
>> Am 21.04.2008 um 14:50 schrieb John Fox:
>>> Dear Brigit,
>>>
>>> My guess is that you forgot to specify the argument
>>> family=binomial in
>>> the call to glm().
>>>
>>> Had you included the commands that you used as well as the error
>>> that
>>> was produced, it wouldn't be necessary to guess.
>>>
>>> I hope this helps,
>>> John
>>>
>>> On Mon, 21 Apr 2008 14:23:13 +0200
>>> Birgit Lemcke <birgit.lemcke at systbot.uzh.ch> wrote:
>>>> R version 2.6.2 PowerBook G4
>>>>
>>>> Hello R User,
>>>>
>>>> I try to perform an ANCOVA using the glm function.
>>>> I have a dataset with continuous and categorical data (explanatory
>>>> variables) and my response variable is also binary categorical.
>>>>
>>>> Fehler: NA/NaN/Inf in externem Funktionsaufruf (arg 4)
>>>> Zusätzlich: Warning messages:
>>>> 1: In Ops.factor(y, mu) : - nicht sinnvoll für Faktoren (makes no
>>>> sense for factors)
>>>> 2: In Ops.factor(eta, offset) : - nicht sinnvoll für Faktoren
>>>> 3: In Ops.factor(y, mu) : - nicht sinnvoll für Faktoren
>>>>
>>>> My dataset contains NA`s but if I try to use na.exclude, I got the
>>>> same Error message.
>>>>
>>>> I thought the function should use with my dataset. What am I doing
>>>> wrong?
>>>>
>>>> Thanks in advance for your help.
>>>>
>>>> Birgit
>>>>
>>>>
>>>> Birgit Lemcke
>>>> Institut für Systematische Botanik
>>>> Zollikerstrasse 107
>>>> CH-8008 Zürich
>>>> Switzerland
>>>> Ph: +41 (0)44 634 8351
>>>> birgit.lemcke at systbot.uzh.ch
>>>>
>>>> 175 Jahre UZH
>>>> «staunen.erleben.begreifen. Naturwissenschaft zum Anfassen.»
>>>> MNF-Jubiläumsevent für gross und klein.
>>>> 19. April 2008, 10.00 Uhr bis 02.00 Uhr
>>>> Campus Irchel, Winterthurerstrasse 190, 8057 Zürich
>>>> Weitere Informationen http://www.175jahre.uzh.ch/naturwissenschaft
>>>>
>>>> ______________________________________________
>>>> R-help at 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.
>>>
>>> --------------------------------
>>> John Fox, Professor
>>> Department of Sociology
>>> McMaster University
>>> Hamilton, Ontario, Canada
>>> http://socserv.mcmaster.ca/jfox/
>>
>> Birgit Lemcke
>> Institut für Systematische Botanik
>> Zollikerstrasse 107
>> CH-8008 Zürich
>> Switzerland
>> Ph: +41 (0)44 634 8351
>> birgit.lemcke at systbot.uzh.ch
>>
>> 175 Jahre UZH
>> «staunen.erleben.begreifen. Naturwissenschaft zum Anfassen.»
>> MNF-Jubiläumsevent für gross und klein.
>> 19. April 2008, 10.00 Uhr bis 02.00 Uhr
>> Campus Irchel, Winterthurerstrasse 190, 8057 Zürich
>> Weitere Informationen http://www.175jahre.uzh.ch/naturwissenschaft
>>
>> ______________________________________________
>> R-help at 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.
> --
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> Dr. Gavin Simpson [t] +44 (0)20 7679 0522
> ECRC, UCL Geography, [f] +44 (0)20 7679 0565
> Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
> Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/
> UK. WC1E 6BT. [w] http://www.freshwaters.org.uk
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>
Birgit Lemcke
Institut für Systematische Botanik
Zollikerstrasse 107
CH-8008 Zürich
Switzerland
Ph: +41 (0)44 634 8351
birgit.lemcke at systbot.uzh.ch
175 Jahre UZH
«staunen.erleben.begreifen. Naturwissenschaft zum Anfassen.»
MNF-Jubiläumsevent für gross und klein.
19. April 2008, 10.00 Uhr bis 02.00 Uhr
Campus Irchel, Winterthurerstrasse 190, 8057 Zürich
Weitere Informationen http://www.175jahre.uzh.ch/naturwissenschaft
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