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null model for testing nestedness

3 messages · v_coudrain at voila.fr, Jari Oksanen

Original
v_coudrain at voila.fr
# 
Thank you very much. Yes it is working with oecosimu, exept that it does not seem to work for weighted data. There is the possibility to specify "weighted = TRUE": 

oecosimu(matrix,nestednodf, method = "quasiswap", nsimul = 999, order = FALSE, weighted =TRUE)

However, I get only null values and p=1. For weighted = F, I get good values.

Best wishes
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Jari Oksanen
# 
Valerie,

There are at least two problems here: the way you call oecosimu() and how nestdnodf(..., weighted =TRUE) works with binary data. 

If you specify a *binary* null model as method, then you will get binary data. Even if you supplied quantitative data, they are transformed into 1/0 (presence/absence) data. You specified method = "quasiswap", and that is binary model. Another problem is that nestednodf(..., weighted = TRUE) seems to evaluate the statistics all as zeros if you request weighted (= quantitative data) analysis of non-quantitative data (binary). It cannot perform weighted analysis if there are no weights, but still I think it should return something else than zeros. We'll have a look at that issue. 

You should specify a non-binary null model if you want to have a non-binary (weighted) analysis. Quantitative null models are problematic, and vegan release version does not have much choice here. I think "r2dtable" may be the only one. Development version of vegan in http://www.r-forge.r-project.org/ has a wider gamme of non-binary null models, but I think you need to be brave to use quantitative null models. They are something for people who are not afraid of going to areas where angels fear to tread.

FWIW, weighted nestednodf seems to work in oecosimu if you ask for a quantitative nullmodel ("r2dtable" in my tests) both with the release version (2.0-8 or 2.0-9) and with the development version (2.1-35 or 2.1-36). But you really need to to specify a quantitative null model. Both null models and oecosimu are completely re-written and re-designed in development versions.

Cheers, Jari Oksanen

On 25/09/2013, at 15:56 PM, <v_coudrain at voila.fr>
 wrote:
v_coudrain at voila.fr
# 
Dear Jari,

Thank you very much for this clear answer. I did not get that quasiswap only concerned binary data. After reading your explanations, I think I'll stay to binary 
data and avoid the issue of weighted ones, which are much less straightforward to interpret. Anyway, I will have a look at the development versions.

Best wishes,
Val?rie
(presence/absence) data. You specified method = "quasiswap", and that is binary model. Another problem is that nestednodf(..., weighted = TRUE) seems to 
evaluate the statistics all as zeros if you request weighted (= quantitative data) analysis of non-quantitative data (binary). It cannot perform weighted analysis if 
there are no weights, but still I think it should return something else than zeros. We'll have a look at that issue.
version does not have much choice here. I think "r2dtable" may be the only one. Development version of vegan in http://www.r-forge.r-project.org/ has a wider 
gamme of non-binary null models, but I think you need to be brave to use quantitative null models. They are something for people who are not afraid of going to 
areas where angels fear to tread.
2.0-9) and with the development version (2.1-35 or 2.1-36). But you really need to to specify a quantitative null model. Both null models and oecosimu are 
completely re-written and re-designed in development versions.
TRUE":
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