View source: R/likelihood_t_DD.R
likelihood_t_DD | R Documentation |
Computes the likelihood of a dataset under either the linear or exponential diversity dependent model with specified sigma2
and slope values.
likelihood_t_DD(phylo, data, par,model=c("DDlin","DDexp"))
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 |
model |
model chosen to fit trait data, |
When specifying par
, log(sig2)
must be listed before the slope parameter (b
or r
).
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 slope 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
Weir, J. & Mursleen, S. 2012. Diversity-dependent cladogenesis and trait evolution in the adaptive radiation of the auks (Aves: Alcidae). Evolution 67:403-416.
fit_t_comp
likelihood_t_DD_geog
data(Anolis.data) phylo <- Anolis.data$phylo pPC1 <- Anolis.data$data # Compute the likelihood that the r value is twice the ML estimate for the DDexp model par <- c(0.08148371, (2*-0.3223835)) lh <- -likelihood_t_DD(phylo,pPC1,par,model="DDexp")
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