Re: [R-sig-eco] Random Forest classification on species counts

I have also had some luck with using unsupervised random forest to get a proximity matrix. This proximity matrix can then be transformed into a distance matrix, and used as an input to PCO or NMDS. e.g. require(ecodist) urf = randomForest(FY09Bugs[, 2:146]) site_distances = as.dist(1 -

[R-sig-eco] anova.cca question / missing data in constraining matrix

Hello, I am using the cca function in Vegan to examine the relationship between microbial community structure and a (large) suite of environmental variables. My constraining/environmental data matrix as a lot of holes in it so I have been exploring using the na.action argument. This is the

[R-sig-eco] Question on GLMM

Dear Friends, I am new on R so I ask you to excuse me if this question sounds fool. I want to see if there is a significativa relationship between the mating (response variable) and several explanatory variables such as individual number (categorical), leg movemente (continous) and the reuse of

Re: [R-sig-eco] anova.cca question / missing data in constraining matrix

Hello, On 01/06/2013, at 02:10 AM, ckellogg wrote: Hello, I am using the cca function in Vegan to examine the relationship between microbial community structure and a (large) suite of environmental variables. My constraining/environmental data matrix as a lot of holes in it so I have been