likelihood_t_MC_geog {RPANDA}

Likelihood of a dataset under the matching competition model with biogeography.

Description

Computes the likelihood of a dataset under the matching competition model with specified sigma2 and S values and with a geography.object formed using CreateGeoObject.

Usage

likelihood_t_MC_geog(phylo, data, par,geo.object)

Arguments

phylo

an object of type 'phylo' (see ape documentation)

data

a named vector of continuous data with names corresponding to phylo$tip.label

par

a vector listing a value for log(sig2) (see Note) and S (parameters of the matching competition model), in that order

geo.object

a geography object indicating sympatry through time, created using CreateGeoObject

Details

When specifying par, log(sig2) must be listed before S.

Value

the negative log-likelihood value of the dataset (accordingly, the negative of the output should be recorded as the likelihood), given the phylogeny, sig2 and S values, and geography.object.

Note

S must be negative (if it is positive, the likelihood function will multiply input by -1).

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).

Author(s)

Jonathan Drury [e-mail]

Julien Clavel

References

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.

See Also

fit_t_comp CreateGeoObject likelihood_t_MC

Examples

data(Anolis.data)
phylo <- Anolis.data$phylo
pPC1 <- Anolis.data$data
geography.object <-  Anolis.data$geography.object

# Compute the likelihood with geography using ML parameters for fit without geography
par <- c(0.0003139751, -0.06387258)
lh <- -likelihood_t_MC_geog(phylo,pPC1,par,geography.object)