In R the PhyloPars package might be interesting. Haven’t used it... though.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703881/
Cheers Franz
Sent from my mobile
> On 31. Jul 2018, at 21:04, Nicolay Cunha <nicolaycu...@gmail.com> wrote:
>
> Dear list members,
>
> I would like to test a linear model between a predictor variable (e.g.
> altitude) and a dependent variable (e.g. number of flowers). For this, I do
> have several observations of individuals of 42 species along the predictor
> variable, but the number of observations do vary per each species and class
> of the independent variable. In the end, I do have 364 observations
> unbalanced per each of the 42 species and environment.
>
> My intention is doing a model having the number of flower as dependent
> variable, the temperature as fixed effect, using species as a random factor
> and add a phylogenetic correction. I could do part of this this using GLS,
> but the fact of having multiple observations per species do not allow
> running the model and returns the following message:
>
>
> *“number of observations and number of tips in the tree are not equal.”*
> I would much appreciate if you could give me advices on how to overcome
> this issue and run such model.
>
> Many thanks,
>
> Nicolay
>
> Grupo de Ecología de la Polinización, INIBIOMA,
> CONICET-Universidad Nacional del Comahue,
> Quintral 1250, 8400 San Carlos de Bariloche, Rio Negro, Argentina
>
> #**************************************************************************************#
>
> # Below an example code
>
>
>
>
>
>
> *library(phytools)tree <- rtree(5, rooted = FALSE, tip.label =
> LETTERS[1:5])x <- data.frame( spp = c(sample(c(LETTERS [1:3]),100,
> replace = T), sample(c(LETTERS [2:4]),100, replace =
> T), sample(c(LETTERS [3:5]),100, replace = T)),
> alt = rep(c("1000", "1500", "2000"), each = 100),*
>
>
>
> * flower = rnorm(300)) library(nlme)fit <- gls(flower ~ alt,
> correlation = corPagel(1,tree, fixed=FALSE), method="ML", data = x) *
>
>
> #**************************************************************************************#
>
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>
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