plot_pvo {bite}

Plots estimates of species traits distribution

Description

Density plot representing estimated species trait distributions under a jive model. This function plots the mean or median density distribution and the HPD distributions assuming that the trait is normally distributed

Usage

plot_pvo(phy, traits, map = NULL, mcmc.log, tip = NA, burnin = 0.1,
  conf = 0.95, stat = "median", trait.lab = "x", col = NULL,
  lab = TRUE, lolipop = c(0.4, 0.4), cex.tip = par("cex"),
  var.f = NULL, ...)

Arguments

phy

phylogenetic tree provided as either a simmap or a phylo object

traits

trait data used to perform the jive analysis. This has to be of the same form as the one used in make_jive

map

map used to perform the jive analysis. This has to be of the same form as the one used in make_jive

mcmc.log

the output file of a mcmc_bite run

tip

A string giving the species to be plotted. If tip == NA, the posterior distribution of every tip is plotted along with the phylogenetic tree

burnin

The size of the burnin in number of iterations or the proportion of iteration you want to remove

conf

A number of [0,1] giving the confidence level desired.

stat

A character giving the function to be used to estimate species mean and variance from the posterior distributions. Must be one of be "mean" and "median"

trait.lab

a charachter specifying the axis label for the traits

col

color of the density filling. Must be of size two for estimates and HPD. If col and border are NULL, two random colors are assigned

lab

logical indicating whether to show species name in the plot. Only evaluated if tip =! NA

lolipop

size and width of the lolipops representing samples

cex.tip

size of the tips

var.f

alternative distribution used to model intraspecific variation of the form function(n, pars). The function must return n samples from the given distribution.

...

Additional parameters that can be parsed to plot

Author(s)

Theo Gaboriau

Examples

## Load test data
data(Anolis_traits)
data(Anolis_tree)
data(Anolis_map)
# Run a simple MCMC chain
my.jive <- make_jive(Anolis_tree, Anolis_traits[,-3],  model.priors=list(mean="BM", logvar = "OU"))
bite_ex <- tempdir()
logfile <- sprintf("%s/my.jive_mcmc.log", bite_ex)
mcmc_bite(my.jive, log.file=logfile, sampling.freq=1, print.freq=1, ngen=500) 
# import the results in R
res <- read.csv(logfile, header = TRUE, sep = "\t")
 plot_pvo(phy = Anolis_tree, traits = Anolis_traits, tip = NA, mcmc.log = res)