rcpp_calc_splitlikes_using_COOweights_columnar {cladoRcpp}R Documentation

Calculate the split likelihoods using COO_weights_columnar


Calculates the split likelihoods using COO_weights_columnar, i.e. the weights as produced by rcpp_calc_anclikes_sp_COOweights_faster.


  Rcpp_rightprobs, COO_weights_columnar, Rsp_rowsums, printmat = TRUE)



Probabilities of the states at the base of the left descendant branch


Probabilities of the states at the base of the right descendant branch


Transition probability matrix in COO-like format as 4 columns: ancestral index, left index, right index, conditional probability given ancestral states. (assuming likelihood of descendants is 1). Indexes are 0-based. Keep in mind that cladogenesis matrices exclude the null state (a range of 0 areas), so if your states list starts with the null range (as is typical/default in DEC-style models) then to get the R 1-based state indices requires e.g. COO_weights_columnar[[1]] + 2.


A vector of size (numstates) giving the sum of the relative probabilites of each combination of descendant states, assuming the probabilities of the left- and right-states are all equal (set to 1). This is thus the sum of the weights, and dividing by this normalization vector means that the each row of the speciation probability matrix will sum to 1. Default assumes the weights sum to 1 but this is not usually the case. Rsp_rowsums need only be calculated once per tree+model combination, stored, and then re-used for each node in the tree, yielding significant time savings.


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...)


splitlikes Vector of the probabilities of each allowed split


Nicholas Matzke matzke@berkeley.edu

See Also

rcpp_calc_anclikes_sp #bibliography /Dropbox/_njm/__packages/cladoRcpp_setup/cladoRcpp_refs.bib @cite Matzke_2013 @cite Matzke_2014


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

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

[Package cladoRcpp version 0.15.1 Index]