fitdAICrc.batch {laser} | R Documentation |
Generates null distribution of dAICrc test statistic and determines significance of dAICrc indices calculated for 'real' phylogenies.
fitdAICrc.batch(x, modelset = c("pureBirth", "bd", "DDL", "DDX", "yule2rate"), verbose = TRUE, file = "out_daic.batch.txt", ints = NULL, alternative = NULL, stat = NULL)
x |
a numeric matrix or dataframe of branching times |
modelset |
the set of rate-constant and rate-variable candidate models to be fitted |
verbose |
write output to file (recommended) |
file |
a filename for output if 'verbose = TRUE' |
ints |
the number of shift points to consider |
alternative |
specifies one or two-tailed Ho test |
stat |
the dAICrc statistic for the 'real' phylogeny |
For details on input format, see getBtimes.batch
. The modelset should
be identical to that used to compute the dAICrc for the test phylogeny.
'verbose' generates an output file, specified by 'file', and contains parameter and likelihood summaries for each set of branching times. It is highly recommended that you leave verbose = TRUE, unless you have a reason not to.
'alternative' is only applicable if you are entering a calculated dAICrc value for a test phylogeny (see 'stat' below. The default ('alternative = NULL') implements a two-tailed test of the null hypothesis that rates have not changed over time. You can also specify alternative = 'decrease' or alternative = 'increase' if you want a one-tailed test of the null hypothesis that rates have not decreased (or increased) over time.
'stat' is the calculated dAICrc statistic obtained for a test phylogeny for which you would like to
obtain a p-value (using fitdAICrc
).
A dataframe with N rows, where N is the number of sets of branching times analyzed. Columns of the data frame contain the following elements (and are accessed using the names given below):
dAICrc |
the calculated dAICrc statistic for dataset i |
rcbest |
the AIC score for the best rate-constant model |
rvbest |
the AIC score for the best rate-variable model |
bestmodel |
the best-fit model as determined by the AIC |
sp |
general diversification pattern specified by the best-fit model. 'NC' is no change in rate, 'RD' is rate decrease, and 'RI' is rate-increase |
LpureBirth |
the maximum log-likelihood under the pure birth model |
Lbd |
the maximum log-likelihood under the rate-constant birth-death model |
L<model> |
Other model log-likelihoods abbreviated as above... |
Computational time required to generate the null distribution of dAICrc can be high
if the number of phylogenies is large (>5000) and if rvbd
and/or yule3rate
models
are included in the candidate set.
Ensure that your 'ints' settings are identical to those used to generate the dAICrc
statistic for the test phylogeny (fitdAICrc
).
fitdAICrc.batch
will print details of run progress to screen, but you
must ensure that you turn off the 'buffered output' option under the 'Misc'
pull-down menu in the R GUI.
Dan Rabosky DLR32@cornell.edu
Rabosky, D. L. 2006. Likelihood methods for inferring temporal shifts in diversification rates. Evolution 60:1152-1164.
data(rtrees50) write.table(rtrees50, file = 'temp.txt', quote=FALSE, row.names = FALSE, col.names = FALSE) bt <- getBtimes.batch(file = 'temp.txt', format = 'newick') # using 'string' option to get branching times. bt is now a dataframe # of branching times, where rows are trees. result <- fitdAICrc.batch(bt, modelset = c("pureBirth", "bd", "DDX", "DDL", "yule2rate"), ints = 20) # fits 2 rate-constant and 3 rate variable models to each of the # 50 trees in the example datafile 'rtrees50' and generates # the distribution of dAICrc from the sample.