getMAPS_ClaDS0 function

Gets the Maximum A Posteriori for each ClaDS0 parameter

Extract the MAPs (Maximum A Posteriori) for the marginal posterior distributions estimated with run_ClaDS0.

getMAPS_ClaDS0(phylo, sampler, burn=1/2, thin=1)

Arguments

• phylo: An object of class 'phylo'.
• sampler: The output of a run_ClaDS0 run.
• burn: Number of iterations to drop in the beginning of the chains.
• thin: Thinning parameter, one iteration out of "thin" is kept to compute the MAPs.

Returns

A vector MAPS containing the MAPs for the marginal posterior distribution for each of the model's parameters.

MAPS[1:3] are the estimated hyperparameters, with MAPS[1] the sigma parameter (new rates stochasticity), MAPS[2] the alpha parameter (new rates trend), and MAPS[3] the initial speciation rate lambda_0.

MAPS[-(1:3)] are the estimated branch-specific speciation rates, given in the same order as the phylo$edges.

References

Maliet O., Hartig F. and Morlon H. 2019, A model with many small shifts for estimating species-specific diversificaton rates, Nature Ecology and Evolution, doi 10.1038/s41559-019-0908-0

Author(s)

O. Maliet

See Also

fit_ClaDS0, plot_ClaDS0_chains, getMAPS_ClaDS

Examples

set.seed(1)

if(test){
obj= sim_ClaDS( lambda_0=0.1,    
                mu_0=0.5,      
                sigma_lamb=0.7,         
                alpha_lamb=0.90,     
                condition="taxa",    
                taxa_stop = 20,    
                prune_extinct = TRUE)  

tree = obj$tree
speciation_rates = obj$lamb[obj$rates]
extinction_rates = obj$mu[obj$rates]
data("ClaDS0_example")

# extract the Maximum A Posteriori for each of the parameters
MAPS = getMAPS_ClaDS0(ClaDS0_example$tree, 
                      ClaDS0_example$Cl0_chains, 
                      thin = 10)

# plot the simulated (on the left) and inferred speciation rates (on the right)
# on the same color scale
plot_ClaDS_phylo(ClaDS0_example$tree, 
          ClaDS0_example$speciation_rates, 
          MAPS[-(1:3)])
}