rcpp_calc_anclikes_sp_COOprobs: Faster version of rcpp_calc_anclikes_sp

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

View source: R/cladoRcpp.R

Description

This function is a faster version of rcpp_calc_anclikes_sp. Like rcpp_calc_anclikes_sp, this function calculates the conditional probability of every allowed combination of ancestral range, left descendent range, and right descendent range.

Usage

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  rcpp_calc_anclikes_sp_COOprobs(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)

Arguments

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...)

Details

This function improves upon rcpp_calc_anclikes_sp by returning a COO-like list of the nonzero cells in the transition matrix for the speciation event.

(COO = Coordinate list format for a matrix, see http://en.wikipedia.org/wiki/Sparse_matrix#Coordinate_list_.28COO.29

Whereas a COO-formatted square matrix stores, for each nonzero cell, the row #, column #, and cell value, rcpp_calc_anclikes_sp returns lists containing, for each nonzero cell:

1. 0-based index of the ancestral state
2. 0-based index of the left state
3. 0-based index of the right state
4. Value of the specified nonzero cell

Time savings over rcpp_calc_anclikes_sp are realized by skipping many ancestor/descendent combinations which are impossible transitions on the model, and neither recording, nor storing, nor passing them. This becomes important with large state spaces.

Value

list_weights_of_transitions A list of 3 lists. Each list has (numstates) items, representing the ancestral states. List #1 gives the 0-based state index for the nonzero left descendents of each ancestral state. List #2 gives the 0-based state index for the nonzero right descendents of each ancestral state. List #3 gives the weight of each nonzero transition from each ancestral state. Summing these weights within each ancestral state for list #3 gives the total of the weights for each ancestral state. Dividing the weights by the sum of weights gives the conditional probability of each descendent state, conditional on the ancestral state. These conditional probabilities need only be calculated once per tree+model combination, stored, and then re-used for each node in the tree, yielding significant time savings.

Author(s)

Nicholas Matzke matzke@berkeley.edu

References

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>.

See Also

rcpp_calc_anclikes_sp, rcpp_calc_anclikes_sp_COOprobs, rcpp_calc_anclikes_sp_COOweights_faster

Examples

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# 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.