rcpp_calc_anclikes_sp_COOprobs {cladoRcpp} | R Documentation |
Faster version of rcpp_calc_anclikes_sp
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
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 |
v |
Relative weight of vicariant speciation. Default |
j |
Relative weight of "founder event speciation"/jump speciation. Default |
y |
Relative weight of fully sympatric speciation (range-copying). Default |
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
|
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 |
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 |
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 |
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 |
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
See Also
rcpp_calc_anclikes_sp
, rcpp_calc_anclikes_sp_COOprobs
,
rcpp_calc_anclikes_sp_COOweights_faster
#bibliography /Dropbox/_njm/__packages/cladoRcpp_setup/cladoRcpp_refs.bib
@cite Matzke_2013
@cite Matzke_2014
@cite ReeSmith2008
Examples
# 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