rcpp_calc_anclikes_sp_COOweights_faster: Even faster version of rcpp_calc_anclikes_sp
In wrathematics/cladoRcpp: C++ implementations of phylogenetic calculations

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

This function improves on rcpp_calc_anclikes_sp and rcpp_calc_anclikes_sp_COOprobs. In addition to the compressed COO-like storage format, the internal C++ code here explicitly enumerates the allowed transitions, rather than searching through every possibility and testing whether or not it is allowed. This appears to scale well to very large state spaces.

  rcpp_calc_anclikes_sp_COOweights_faster(Rcpp_leftprobs,
    Rcpp_rightprobs, l, s = 1, v = 1, j = 0, y = 1,
    dmat = NULL, maxent01s = NULL, maxent01v = NULL,
    maxent01j = NULL, maxent01y = NULL,
    max_minsize_as_function_of_ancsize = NULL,
    printmat = TRUE)

`Rcpp_leftprobs`	Probabilities of the states at the base of the left descendant branch
`Rcpp_rightprobs`	Probabilities of the states at the base of the right descendant branch
`l`	List of state indices (0-based)
`s`	Relative weight of sympatric "subset" speciation. Default `s=1` mimics LAGRANGE model.
`v`	Relative weight of vicariant speciation. Default `v=1` mimics LAGRANGE model.
`j`	Relative weight of "founder event speciation"/jump speciation. Default `j=0` mimics LAGRANGE model.
`y`	Relative weight of fully sympatric speciation (range-copying). Default `y=1` mimics LAGRANGE model.
`dmat`	If given, a matrix of rank numareas giving multipliers for the probability of each dispersal event between areas. Default NULL, which sets every cell of the `dmat` matrix to value 1. Users may construct their own parameterized `dmat` (for example, making `dmat` a function of distance) for inclusion in ML or Bayesian analyses.
`maxent01s`	Matrix giving the relative weight of each possible descendant rangesize for the smaller range, for a given ancestral rangesize, for a subset-sympatric speciation event. Default is `NULL`, which means the script will set up the LAGRANGE model (one descendent always has range size 1).
`maxent01v`	Matrix giving the relative weight of each possible descendant rangesize for the smaller range, for a given ancestral rangesize, for a vicariance speciation event. Default is `NULL`, which means the script will set up the LAGRANGE model (one descendent always has range size 1).
`maxent01j`	Matrix giving the relative weight of each possible descendant rangesize for the smaller range, for a given ancestral rangesize, for a founder-event speciation event. Default is `NULL`, which means the script will set up the LAGRANGE model (one descendent always has range size 1).
`maxent01y`	Matrix giving the relative weight of each possible descendant rangesize for the smaller range, for a given ancestral rangesize, for a full-sympatric (range-copying) speciation event. Default is `NULL`, which means the script will set up the LAGRANGE model (one descendent always has range size 1).
`max_minsize_as_function_of_ancsize`	If given, any state with a range larger that this value will be given a probability of zero (for the branch with the smaller rangesize). This means that not every possible combination of ranges has to be checked, which can get very slow for large state spaces.
`printmat`	Should the probability matrix output be printed to screen? (useful for debugging, but can be dramatically slow in R.app for some reason for even moderate numbers of states; perhaps overrunning the line length...)

This should be faster, i.e. by look for each type of event individually.

Returns results as 4 columns: ancestral index, left index, right index, conditional probability given ancestral states (assuming likelihood of descendants is 1). Indexes are 0-based.

When the calculation is run at each node in the tree, all that is required is one pass through the COO-like array, with the downpassed probabilities of the states on the left and right branches multiplied by the probability column.

COO_weights_columnar Transition weights matrix in COO-like format as 4 columns: ancestral index, left index, right index, and weight of the specified transition. Indexes are 0-based. Dividing the weights by the sum of the weights for a particular ancestral state yields the conditional probabilities of each transition at the speciation event. (assuming likelihood of descendants is 1).

Nicholas Matzke matzke@berkeley.edu

Matzke N (2012). "Founder-event speciation in BioGeoBEARS package dramatically improves likelihoods and alters parameter inference in Dispersal-Extinction-Cladogenesis (DEC) analyses." _Frontiers of Biogeography_, *4*(suppl. 1), pp. 210. ISSN 1948-6596, Poster abstract published in the Conference Program and Abstracts of the International Biogeography Society 6th Biannual Meeting, Miami, Florida. Poster Session P10: Historical and Paleo-Biogeography. Poster 129B. January 11, 2013, <URL: http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster>.

Ree RH and Smith SA (2008). "Maximum likelihood inference of geographic range evolution by dispersal, local extinction, and cladogenesis." _Systematic Biology_, *57*(1), pp. 4-14. <URL: http://dx.doi.org/10.1080/10635150701883881>, <URL: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18253896>.

rcpp_calc_anclikes_sp, rcpp_calc_anclikes_sp_COOprobs, rcpp_calc_anclikes_sp_COOweights_faster

rcpp_calc_anclikes_sp

# For the basic logic of a probablistic cladogenesis model, see
?rcpp_calc_anclikes_sp

# For examples of running the functions, see the comparison of all functions at:
# ?cladoRcpp

wrathematics/cladoRcpp documentation built on May 4, 2019, 9:48 a.m.