Hello Stephen,

I am happy that you help me. Thanks a million.

It is a good feeling that you confirm my assumption that dsvdis is  
not able to deal with missing data, because it says me that I am not  
completely incapable.
Okay now I have the problem what to do.
I used this function ´cause there is an option to weight columns  
differently what I haven´t found in other functions.

But now I don´t understand why I have to transpose the species as  
columns? As I read in the help manual of dsvdis this function  
calculates dissimilarities between rows.
I have to calculate the dissimilarities between species that are in  
rows by the use of morphological characters that are in columns.

Am I completely wrong with my thoughts?

Birgit

Am 20.06.2007 um 15:52 schrieb Stephen B. Cox:

> Hi Birgit - looks like you have a few issues here.
>
> Birgit Lemcke <birgit.lemcke <at> systbot.uzh.ch> writes:
>
>>
>> Hello you all!
>>
>> I am a completely new user of R and I have a problem to solve.
>> I am using Mac OS X on a PowerBook.
>>
>> I have a table that looks like this:
>>
>>             species X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14
>> X15 X16 X17 X18 X19 X20 X21
>> 1        Anth_cap1  1  0  0  1  0  1  0  0  1   0   0   0   0   0
>> 0   0   1   0   0   0   1
>> 2       Anth_crin1  1  0  0  1  0  1  0  0  1   0   1   0   0   0
>> 0   0   0   1   0   0   1
>> 3        Anth_eck1  1  0  0  1  0  1  0  0  1   0   0   0   0   0
>> 0   0   0   1   0   0   1
>> 4       Anth_gram1  1  0  0  1  0  1  0  0  1  NA  NA  NA  NA   0
>> 0   0   0   1   0   0   0
>> 5       Anth_insi1  1  0  0  1  0  1  0  0  1   0   0   0   1   0
>> 0   0   0   1   0   0   1
>>
>> All columns  are binary coded characters.
>> The Import was done by this
>>
>> Test<-read.table("TestRFemMalBivariat1.csv",header = TRUE, sep = ";")
>
> First - you need to transpose the matrix to have species as  
> columns.  You can do
> this with:
>
> d2 = data.frame(t(Test[,-1]))
> colnames(d2) = Test[,1]  #now use d2
>
>
>
>> Now I try to perform a similarity analysis with the dsvdis function
>> of the labdsv package with the sorensen-Index.
>>
>> My first question is if all zeros in my table are seen as missing
>> values and if it islike that how can I change without turning zero
>> into other numbers?
>
> no - the zeros are valid observations.  the na's are missing data.
>
>
>>   DisTest<-dsvdis(Test, index = "sorensen")
>>
>> But I always get back this error message:
>>
>> Warnung in symbol.For("dsvdis") :'symbol.For' is not needed: please
>> remove it
>> Fehler in dsvdis(Test, index = "sorensen") :
>> 	NA/NaN/Inf in externem Funktionsaufruf (arg 1)
>> Zusätzlich: Warning message:
>> NAs durch Umwandlung erzeugt
>
>
>
> Second - you have an issue with missing data.  It looks like dsvdis  
> does not
> like the NA's - so you must make a decision about what to do.   
> Delete that
> species, delete that site, or whatever...
>
> Finally - the warning over symbol.For is an issue with the labdsv  
> library itself
> - nothing you are doing wrong.  The results will still be valid -  
> but the use of
> symbol.For is something that will eventually need to be changed in  
> the labdsv
> library.
>
> hth,
>
> stephen

Birgit Lemcke
Institut für Systematische Botanik
Zollikerstrasse 107
CH-8008 Zürich
Switzerland
Ph: +41 (0)44 634 8351
birgit.lemcke@systbot.uzh.ch






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