rtt(t, tip.dates, ncpu = 1, objective = correlation, opt.tol = .Machine$double.eps^0.25)"phylo".t, in the same order as t$tip.label."correlation", "rms", or
"rsquared"."phylo".
t must have branch lengths in units of expected substitutions
per site.
tip.dates should be a vector of sampling times, in any time
unit, with time increasing toward the present. For example, this may
be in units of ``days since study start'' or ``years since 10,000
BCE'', but not ``millions of yearsago''.
Setting ncpu to a value larger than 1 requires the parallel
library.
objective is the measure which will be used to define the
``goodness'' of a regression fit. It may be one of "correlation"
(strongest correlation between tip date and distance from root),
"rms" (lowest root-mean-squared error), or "rsquared"
(highest R-squared value).
opt.tol is used to optimize the location of the root along the best
branch. By default, R's optimize function uses a precision of
.Machine$double.eps^0.25, which is about 0.0001 on a 64-bit system.
This should be set to a smaller value if the branch lengths of t are
very short.
Rambaut, A. (2000). Estimating the rate of molecular evolution: incorporating non-contemporaneous sequences into maximum likelihood phylogenies. Bioinformatics, 16, 395-399.
t <- rtree(100)
tip.date <- rnorm(t$tip.label)^2
rtt(t, tip.date)
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