Re: [R-sig-eco] Calculate AIC, DIC and BIC for models machine learning

Hi Lara, Sarah There is a problem in estimation of degrees of freedom so even though some people try to estimate AIC eg for Maxent models, it's not correct (the number of parameters in the model is not the effective degrees of freedom). Same for GBM, RF etc. e.g. see Hauenstein, S., Wood, S.N.

[R-sig-eco] Fwd: [EXTERNAL] Which R package for Second-Stage nMDS ?

Pierre-- That's actually an easy question. Look at the vegan package https://cran.r-project.org/web/packages/vegan/index.html. It has functions for various dissimilarity & distance metrics (and can use distance matrices from other packages such as ecodist), MDS and allied processes, anosim and

Re: [R-sig-eco] R-sig-ecology Digest, Vol 132, Issue 10

Prof Dr. Ralf Schäfer thank you for sharing the links. Best regards, Lara Silva Sem vírus. www.avast.com

Re: [R-sig-eco] Which R package for Second-Stage nMDS ?

Thanks a lot dear Philip. I will try this. all the best Pierre Le 22/03/2019 à 17:07, Dixon, Philip M [STAT] a écrit : Pierre, I don't know a function that does this, but it is extremely easy to code. Dist objects are vectors containing the 1st stage pairwise dissimilarities. Call those

[R-sig-eco] Which R package for Second-Stage nMDS ?

Pierre, I don't know a function that does this, but it is extremely easy to code. Dist objects are vectors containing the 1st stage pairwise dissimilarities. Call those dist1, dist2, dist3, ... So alldist <- cbind(dist1=dist1, dist2=dist2, ...) will assemble the matrix of dissimilarities

Re: [R-sig-eco] R-sig-ecology Digest, Vol 132, Issue 10

Hi Lara, I am actually not sure that this is the best way to proceed. Cross-validation seems the method of choice and depending on your purpose you can compare the prediction error between models. See: Hauenstein S., Wood S.N. & Dormann C.F. (2018). Computing AIC for black-box models using

[R-sig-eco] Which R package for Second-Stage nMDS ?

Dear useRs, I want to perform 2nd stage nMDS, as described in Clarke, K.R., et al (2006). Exploring interactions by second-stage community analyses. Journal of Experimental Marine Biology and Ecology 338, 179-192. See Abstract below Do you know a package in R for that ? Or would you have