expectedLTT: Maximun likelihood estimation for a set of trees

In franciscorichter/emphasisR: Expectation Maximization on PHylogenetic Applications with Simulations and Importance Sampling

Description

Bootstrapping to simulate trees and obtain expected LTT plot given a model and its parameter values.

Usage

expectedLTT(pars, ct=15, model, n_it= 100,color="blue",g=ggplot(),all_trees=TRUE)

Arguments

pars	Parameters of the diversification rates.
ct	Age of the clade
model	Species Miversification Model
n_it	Number of simulated trees
color	Color of the lines of the ltt plot
g	Plot to use to add new simulations
all_trees	True if want to add all trees ltt plots. False if only want to add the expected ltt plot

Value

g	A plot with the expected values. ggplot class.

Author(s)

F. Richter M.

Examples

#clade = "Caviidae"
#brts =  get(paste0("brts_",clade))
#pars = as.numeric(DD_est[DD_est$clade==clade,5:7])
#mc = emphasis(brts,model="rpd5c",init_par=c(pars,0),soc=2,sample_size=200,parallel=T)

g = ggplot() + geom_line(data=data.frame(time=-input$brts,n=1:(length(input$brts))),aes(x=time,y=n) )

g1 = expectedLTT(mc$pars,ct=input$brts[1],model = "rpd5c",n_it = 100,color = "Darkgreen",g=g,all_trees = F)
g2 = expectedLTT(as.numeric(DD_est[2,5:7]),ct=input$brts[1],model = "rpd1",n_it = 100,color = "blue",g=g1,all_trees = F)
g2

franciscorichter/emphasisR documentation built on Dec. 20, 2021, 8:50 a.m.