Hi Sheri,
Thank you so much for the extra tools… some of them I already knew, some others don't. 
I appreciate your help!!
S

On Dec 17, 2013, at 12:52 PM, "Sheri O'Connor" <soconnor@lakeheadu.ca> wrote:

> Hi Sol,
> 
> I am assuming that your samples are stratigraphic? You might want to
> check out the rioja package
> http://cran.r-project.org/web/packages/rioja/index.html for
> constrained hierarchical clustering (chclust function) by
> stratigraphic sequence.
> 
> Another idea is biclustering using the method discussed in this paper:
> http://fossil.earthsci.carleton.ca/~tpatters/pubs2/2005/boudreau2005jpaleolimn33_445-461.pdf
> which you can calculate and display with modifications to this:
> http://stats.stackexchange.com/questions/12580/interpretation-of-two-way-clustering-in-r
> 
> Other methods in the Boudreau paper might be useful to test the
> significance of your samples and species.
> 
> HTH,
> Sheri
> 
> On Tue, Dec 17, 2013 at 10:01 AM, Sol Noetinger <s.noetinger@gmail.com> wrote:
>> Hello,
>> 
>> I am trying to apply different statistics methods in a field that traditionally is not very keen to it… and in consequence I am trying to learn all that I can.
>> To the point, I am studying a palynological succession from the Devonian. I have counts of palynomorphs (around 250) from a set of 17 samples. I use the relative abundance to standardise the counting since there are some samples that did have not enough specimens.
>> I have tested cluster analysis with different packages, resulting in two clear groups. I tested the abundance distribution on both groups to see which model fits better.
>> 
>> This is the summary:
>> 
>> Cluster I
>> RAD models, family poisson
>> No. of species 24, total abundance 100
>> 
>>           par1     par2    par3   Deviance AIC     BIC
>> Null                               55.2189      Inf     Inf
>> Preemption    0.1                  85.4721      Inf     Inf
>> Lognormal   0.20534  1.6811         8.0522      Inf     Inf
>> Zipf        0.42497 -1.4264         1.4461      Inf     Inf
>> Mandelbrot  1.4285  -1.8885      1  3.4265      Inf     Inf
>> 
>> Cluster II
>> RAD models, family poisson
>> No. of species 35, total abundance 100
>> 
>>           par1     par2    par3   Deviance AIC     BIC
>> Null                               25.7004      Inf     Inf
>> Preemption    0.1                  27.8760      Inf     Inf
>> Lognormal   0.21756  1.3473         4.7797      Inf     Inf
>> Zipf        0.27724 -1.0959         4.9038      Inf     Inf
>> Mandelbrot  0.64175 -1.3825      1  4.9181      Inf     Inf
>> 
>> I read from the manual that to see which models fits better you use the AIC values.
>> What is the meaning of getting "infinite"?
>> Can I use the Deviance value to compare the models?
>> And in case I can use the deviance, since there are very close values, should I run a test to see if the differences are significant?… in that case, which  one?.
>> 
>> I apologise if my questions are too basic, or if I should refer to a different kind of forum or thread.
>> I hope you can help me, thank you for your time,
>> Regards,
>> 
>> Sol
>> 
>> 
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>> 
>> 
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