bears_2param_DIVA_fast: 2-parameter model, fixed cladogenesis model (as in LAGRANGE)
In BioGeoBEARS: BioGeography with Bayesian (and Likelihood) Evolutionary Analysis in R Scripts

Description Usage Arguments Details Value Note Author(s) References See Also Examples

This function implements a biogeographical model with 2 free parameters (d, rate of dispersal/range addition, and e, rate of extinction/range contraction), and a fixed cladogenesis model copying the DIVA model (Ronquist (1997). This has: equal probability of vicariance at all range sizes, but NO sympatric-subset speciation, no jump/founder-event speciation, and sympatric-range-copying events are limited to the smaller descendant always having a range size of 1 area(Ronquist et al. (2011)).

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  bears_2param_DIVA_fast(trfn = "Psychotria_5.2.newick",
    geogfn = "Psychotria_geog.data", max_range_size = NULL,
    num_cores_to_use = NULL)

`trfn`	The filename of the phylogenetic tree, in NEWICK format (http://evolution.genetics.washington.edu/phylip/newicktree.html). Tipnames should match the names in geogfn. See `read.tree` in APE for reading in phylogenetic trees.
`geogfn`	A PHYLIP-style file with geographic range data (see `getranges_from_LagrangePHYLIP`) for each tipname. This is the same format used by C++ LAGRANGE (SmithRee2010_CPPversion).
`max_range_size`	The maximum rangesize, in number of areas. Having a smaller maximum range size means that you can have more areas (the size of the state space is greatly reduced; see `numstates_from_numareas`.
`num_cores_to_use`	If >1, parallel processing will be attempted. Note: parallel processing via `library (parallel)` will work in Mac command-line R, but not in Mac GUI `R.app`.

Once the model is set up, it is input into the optimization routine optimx (the more common optim can also be used by editing the function), and calc_loglike_sp is used to calculate the log-likelihood of each set of parameters. Once the parameter values that give the data the maximum likelihood are found, they are reported back to the function and returned to the user.

This duplicates the model used in the standard DIVA implementation (Ree et al. (2008), Ree (2009), Smith et al. (2010), with no constraints on dispersal or range size.

Here, all of the fastest processing options have been used.

Model implementations are provided to show the user how a specific model can be set up and optimized. This is preferable compared to the "black-box" nature of most other inference packages. Users are encouraged to experiment. Useful models can be added to later versions of BioGeoBEARS.

bears_output A list of outputs. bears_output$optim_result

Go BEARS!

Nicholas J. Matzke matzke@berkeley.edu

Felsenstein, Joe. The Newick tree format. http://evolution.genetics.washington.edu/phylip/newicktree.html http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster https://code.google.com/p/lagrange/

Ronquist_1997_DIVA

Ronquist_Sanmartin_2011

ReeSmith2008

Ree2009configurator

SmithRee2010_CPPversion

Matzke_2012_IBS

Ronquist1996_DIVA

numstates_from_numareas, getranges_from_LagrangePHYLIP, read.tree, calc_loglike_sp

test=1

# Get the example files directory
extdata_dir = np(system.file("extdata", package="BioGeoBEARS"))
# tmp hard code:
# extdata_dir = "/Dropbox/_njm/__packages/BioGeoBEARS_setup/inst/extdata/"

# Set the filenames (Hawaiian Psychotria from Ree & Smith 2008)
trfn = np(paste(extdata_dir, "/Psychotria_5.2.newick", sep=""))
tr = read.tree(file=trfn)

geogfn = np(paste(extdata_dir, "/Psychotria_geog.data", sep=""))

# Look at the tree and ranges, for kicks
getranges_from_LagrangePHYLIP(lgdata_fn=geogfn)
tr

## Not run: 
# Run the ML search
bears_output = bears_2param_standard_fast(trfn=trfn, geogfn=geogfn)
bears_output

## End(Not run)