rcpp_calc_anclikes_sp_COOweights_faster {cladoRcpp}  R Documentation 
This function improves on rcpp_calc_anclikes_sp
and
rcpp_calc_anclikes_sp_COOprobs
. In addition to the compressed
COOlike 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,
m = NULL, m_null_range = TRUE, jts_matrix = NULL)
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 (0based) 
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 (rangecopying). 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 subsetsympatric 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 founderevent 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 fullsympatric (rangecopying)
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...) 
m 
This is a vector of rate/weight multipliers for dispersal, conditional on the values of some
(nonbiogeographical) trait. For example, one might hypothesize that flight/flightlessness effects
dispersal probability, and manually put a multiplier of 0.001 on the flightlessness state. Or,
one might attempt to estimate this. The strategy used in cladoRcpp is to expand the default cladogenetic
rate matrix by length(m) times. I.e., if m is not 
m_null_range 
Is the null range included in the state space in the general analysis? (The function needs to know this, when there are traits, to index the state space correctly.) 
jts_matrix 
A numtraits x numtraits matrix containing the proportions for trait transitions during j events. E.g., for a sudden switch from trait 1 (flight) to trait 2 (flightlessness) during a jump event. 
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 0based.
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 DECstyle models) then to get the R 1based state indices requires e.g. COO_weights_columnar[[1]] + 2.
When the calculation is run at each node in the tree, all that is required is one pass through the COOlike 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 COOlike format as 4 columns:
ancestral index, left index, right index, and weight of the specified transition. Indexes are
0based.
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 DECstyle models)
then to get the R 1based state indices requires e.g.
COO_weights_columnar[[1]] + 2.
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
rcpp_calc_anclikes_sp
, rcpp_calc_anclikes_sp_COOprobs
,
rcpp_calc_anclikes_sp_COOweights_faster
rcpp_calc_anclikes_sp
#bibliography /Dropbox/_njm/__packages/cladoRcpp_setup/cladoRcpp_refs.bib
@cite Matzke_2013
@cite Matzke_2014
@cite ReeSmith2008
# 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