View source: R/likelihood_t_MC.R
likelihood_t_MC | R Documentation |
Computes the likelihood of a dataset under the matching competition model with specified sigma2
and S
values.
likelihood_t_MC(phylo, data, par)
phylo |
an object of type 'phylo' (see ape documentation) |
data |
a named vector of continuous data with names corresponding to |
par |
a vector listing a value for |
When specifying par
, log(sig2)
must be listed before S
.
the negative log-likelihood value of the dataset (accordingly, the negative of the output should be recorded as the likelihood), given the phylogeny and sig2
and S
values
To stabilize optimization, this function exponentiates the input sig2
value, thus the user must input the log(sig2) value to compute the correct log likelihood (see example).
Jonathan Drury jonathan.p.drury@gmail.com
Julien Clavel
Drury, J., Clavel, J., Manceau, M., and Morlon, H. 2016. Estimating the effect of competition on trait evolution using maximum likelihood inference. Systematic Biology doi 10.1093/sysbio/syw020
Nuismer, S. & Harmon, L. 2015. Predicting rates of interspecific interaction from phylogenetic trees. Ecology Letters 18:17-27.
fit_t_comp
likelihood_t_MC_geog
data(Anolis.data)
phylo <- Anolis.data$phylo
pPC1 <- Anolis.data$data
# Compute the likelihood that the S value is twice the ML estimate
par <- c(0.0003139751, (2*-0.06387258))
lh <- -likelihood_t_MC(phylo,pPC1,par)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.