chronopl  R Documentation 
This function estimates the node ages of a tree using a semiparametric method based on penalized likelihood (Sanderson 2002). The branch lengths of the input tree are interpreted as mean numbers of substitutions (i.e., per site).
chronopl(phy, lambda, age.min = 1, age.max = NULL,
node = "root", S = 1, tol = 1e8,
CV = FALSE, eval.max = 500, iter.max = 500, ...)
phy 
an object of class 
lambda 
value of the smoothing parameter. 
age.min 
numeric values specifying the fixed node ages (if

age.max 
numeric values specifying the oldest bound of the nodes known to be within an interval. 
node 
the numbers of the nodes whose ages are given by

S 
the number of sites in the sequences; leave the default if branch lengths are in mean number of substitutions. 
tol 
the value below which branch lengths are considered effectively zero. 
CV 
whether to perform crossvalidation. 
eval.max 
the maximal number of evaluations of the penalized likelihood function. 
iter.max 
the maximal number of iterations of the optimization algorithm. 
... 
further arguments passed to control 
The idea of this method is to use a tradeoff between a parametric formulation where each branch has its own rate, and a nonparametric term where changes in rates are minimized between contiguous branches. A smoothing parameter (lambda) controls this tradeoff. If lambda = 0, then the parametric component dominates and rates vary as much as possible among branches, whereas for increasing values of lambda, the variation are smoother to tend to a clocklike model (same rate for all branches).
lambda
must be given. The known ages are given in
age.min
, and the correponding node numbers in node
.
These two arguments must obviously be of the same length. By default,
an age of 1 is assumed for the root, and the ages of the other nodes
are estimated.
If age.max = NULL
(the default), it is assumed that
age.min
gives exactly known ages. Otherwise, age.max
and
age.min
must be of the same length and give the intervals for
each node. Some node may be known exactly while the others are
known within some bounds: the values will be identical in both
arguments for the former (e.g., age.min = c(10, 5), age.max =
c(10, 6), node = c(15, 18)
means that the age of node 15 is 10
units of time, and the age of node 18 is between 5 and 6).
If two nodes are linked (i.e., one is the ancestor of the other) and
have the same values of age.min
and age.max
(say, 10 and
15) this will result in an error because the medians of these values
are used as initial times (here 12.5) giving initial branch length(s)
equal to zero. The easiest way to solve this is to change slightly the
given values, for instance use age.max = 14.9
for the youngest
node, or age.max = 15.1
for the oldest one (or similarly for
age.min
).
The input tree may have multichotomies. If some internal branches are of zerolength, they are collapsed (with a warning), and the returned tree will have less nodes than the input one. The presence of zerolengthed terminal branches of results in an error since it makes little sense to have zerorate branches.
The crossvalidation used here is different from the one proposed by
Sanderson (2002). Here, each tip is dropped successively and the
analysis is repeated with the reduced tree: the estimated dates for
the remaining nodes are compared with the estimates from the full
data. For the i
th tip the following is calculated:
\sum_{j=1}^{n2}{\frac{(t_j  t_j^{i})^2}{t_j}}
,
where t_j
is the estimated date for the j
th node
with the full phylogeny, t_j^{i}
is the estimated date
for the j
th node after removing tip i
from the tree,
and n
is the number of tips.
The present version uses the nlminb
to optimise
the penalized likelihood function: see its help page for details on
parameters controlling the optimisation procedure.
an object of class "phylo"
with branch lengths as estimated by
the function. There are three or four further attributes:
ploglik 
the maximum penalized loglikelihood. 
rates 
the estimated rates for each branch. 
message 
the message returned by 
D2 
the influence of each observation on overall date
estimates (if 
The new function chronos
replaces the present one which
is no more maintained.
Emmanuel Paradis
Sanderson, M. J. (2002) Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Molecular Biology and Evolution, 19, 101–109.
chronos
, chronoMPL
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