get.landscape.FPK {BBMV} | R Documentation |
Plots a line representing the adaptive landscape estimated in a BBM+V or an FPK model.
get.landscape.FPK(fit, Npts = 100, main = "Macroevolutionary landscape" , ylab = "N.exp(-V)", xlab = "Trait", xlim = NULL, ylim = NULL) add.ML.landscape.FPK(fit,Npts=100,COLOR=1,LTY='dashed')
fit |
An FPK model fit, as returned by find.mle_FPK. |
Npts |
The number of points used to discretize the trait interval for plotting. |
main |
Title for the plot. |
ylim |
The upper limit of the plotting region when multiple adaptive landscapes are plotted together. |
xlim |
The limits of thex-axis. |
ylab |
Label of the y-axis. |
xlab |
Label of the x-axis. |
COLOR |
The color of the line when added to a plot of the posterior of a MCMC run. |
LTY |
The type of the line when added to a plot of the posterior of a MCMC run. |
A plot of the adaptive landscape across the trait interval.
F. C. Boucher
## Not run: # Simulate data: tree + continuous trait library(geiger) tree=sim.bdtree(stop='taxa',n=10) # tree with few tips for quick tests tree$edge.length=100*tree$edge.length/max(branching.times(tree)) # rescale the tree # Simulate trait evolving on a macroevolutionary landscape with two peaks of equal heights x=seq(from=-1.5,to=1.5,length.out=100) bounds=c(min(x),max(x)) # the bounds we use for simulating V6=10*(x^4-0.5*(x^2)+0.*x) # this is the evolutionary potential: it has two wells TRAIT= Sim_FPK(tree,x0=0,V=V6,sigma=10,bounds=c(-5, 5)) # fit the FPK model: ll_FPK4=lnL_FPK(tree,TRAIT,Npts=25,a=NULL,b=NULL,c=NULL) # the full model fit4=find.mle_FPK(model=ll_FPK4) # Plot the landscape estimated get.landscape.FPK(fit=fit4) ## End(Not run)