null.list = vegan::nullmodel(web,method = "swap_count") %>% simulate(nsim = 50)
null.list = bipartite::nullmodel(web,method = "swap.web",N = 50)
Its much faster with the first function and is there any difference between their results?
null.list = vegan::nullmodel(web,method = "swap_count") %>% simulate(nsim = 50)
null.list = bipartite::nullmodel(web,method = "swap.web",N = 50)
Its much faster with the first function and is there any difference between their results?
Here is my web
> head(D_K.int.el)
209.009185 213.0404912 224.1009612 236.0962499 236.1054269
D_157.0506252 7108 6334 0 4651 -3647
D_165.0193935 5726 6373 0 4453 -3773
D_170.1020846 0 0 0 0 0
D_170.5990132 0 0 0 -4228 0
D_170.8333593 0 3369 3895 5402 -5378
> dim(D_K.int.el)
[1] 200 200
I like to use waldo::compare() to look for differences between objects
Thanks for your answering!
And I have figured it out, the second function is better for me !
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