Re: [R] Dissimilarity

From: Mark Difford <mark_difford_at_yahoo.co.uk>
Date: Wed, 20 Jun 2007 12:49:00 -0700 (PDT)

Hi Birgit,

Just to add to what Gavin has said. There are two other very powerful packages in R that handle this kind of thing: ade4 and vegan. Have a thorough look at both of them. You should be looking at Principal Coordinate Analysis (Classical Scaling) and Non Metric Multidimensional Scaling (NMDS)---with, as Gavin has said, your species as rows. At least the first of these methods goes hand-in-glove with cluster analysis.

Given that you are based in Switzerland, and perhaps are Swiss, you probably therefore read and speak French as a second/third language. You may therefore find the ade4 package more useful, since its authors are French, and its principal authors, Prof. Daniel Chessel &c., have made publicly available some exceptionally useful documentation on these methods on their ade4 website. These are mainly Prof. Chessel's lecture notes:

http://pbil.univ-lyon1.fr/R/enseignement.html

I hope that speeds you on your way.

Regards,
Mark.

PS: Apropos of the Legendre & Legendre text: It's well worth buying if you work in this area; one of its authors, Pierre Legendre, now collaborates with Jari Oksanen on some functions of the vegan package.

Gavin Simpson wrote:

> 
> On Wed, 2007-06-20 at 16:13 +0200, Birgit Lemcke wrote:

>> 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 havent found in other functions.
>>
>> But now I dont 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.
> 
> If you really what to measure the associations between species then
> leave them as you had them as the rows. But make sure you are choosing a
> dissimilarity coefficient that works well for species associations.
> There is a whole section in Legendre and Legendre 1998 Numerical Ecology
> 2nd English Edition Elsevier which may help here.
> 
> HTH
> 
> G
> 

>>
>> 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)
>> >> Zustzlich: 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 fr Systematische Botanik
>> Zollikerstrasse 107
>> CH-8008 Zrich
>> Switzerland
>> Ph: +41 (0)44 634 8351
>> birgit.lemcke_at_systbot.uzh.ch
>>
>>
>>
>>
>>
>>
>> [[alternative HTML version deleted]]
>>
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