Ranked abundance distribution
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 at 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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