rase.slice: Ancestral State Estimation At Any Given Time Slice

Description

Estimates the geographical location of ancestors (at branches or, much less likely, at nodes) at any given point in time integrating over a rase. It first uses tree.slice to identify the branches that the slice intersects with and then uses MCMC sampling to approximate the posterior distribution of the ancestor locations.

Usage

rase.slice(tree, slice, res, polygons, 
	params0 = NA, niter = 1000, logevery = 10, nGQ = 20)

Arguments

tree

phylogenetic tree of class "phylo". The same used in the coderase run.

slice

the time at which to slice. It should be in the same units of the phylogenetic tree.

res

output from rase. Ideally, it should be the post-handled mcmc (i.e., already applied burnin and thinning, if applicable; see post.mcmc).

polygons

list of polygons in owin.object format used as input for rase.

params0

optional. A vector of initial parameter values in the following order: x ancestors for each branch in the order given by tree.slice, followed by y ancestors in the same order.

niter

number of MCMC iterations. By default niter = 1000.

logevery

iteration cycle to print current iteration. By default logevery = 10.

nGQ

degree of the one-dimensional Gauss-Legendre quadrature rule (default = 20) as given by polyCub.SV in package polyCub. Bigger numbers make the integration more precise, but takes longer.

Value

returns a matrix where every column represents one parameter. The first columns (i.e., bX_x; where X = branch 1, ..., branch i) give the ancestral locations for trait x in the order given by tree.slice, followed by the ancestral locations of trait y (i.e., bX_y).

References

Quintero, I., Keil, P., Jetz, W., Crawford, F. W. 2015 Historical Biogeography Using Species Geographical Ranges. Systematic Biology.doi: 10.1093/sysbio/syv057

Examples

Run this code

#load data
data(rase_data, package = 'rase')	
	
## Not run: 
# # check the data we are going to use
# 	
# # examine the mcmc result from rase 
# # after it has been applied a burnin 
# # phase and a thinning
# str(mcmc)
# 	
# # the phylogenetic tree used in the rase run
# psophia_tree
# 
# # the polygons used in the rase run
# str(psophia_poly)
# 		
# # define the slice of time;
# # for now, let's say 1 Million
# # years ago (Ma)
# slice <- 1
# 
# # Species names of polygons (in order)
# pnames <- c('dextralis', 'viridis', 'leucoptera', 'interjecta', 
#   'obscura', 'crepitans', 'ochroptera', 'napensis')
# 
# # name the polygons
# psophia_poly <- name.poly(psophia_poly, psophia_tree, poly.names = pnames)
# 	
# # run rase slice for 100 iterations
# slice_results <- rase.slice(psophia_tree, slice = slice, res = mcmc, 
#       psophia_poly, niter = 100)
# 	
# #check results
# str(slice_results)
# ## End(Not run)