parboot: Estimate of confidence intervals using parametric bootstrap...
In treedater: Fast Molecular Clock Dating of Phylogenetic Trees with Rate Variation

Description Usage Arguments Details Value Author(s) See Also Examples

This function simulates phylogenies with branch lengths in units of substitutions per site. Simulations are based on a fitted treedater object which provides parameters of the molecular clock model. The treedater method is applied to each simulated tree providing a Monte Carlo estimate of variance in rates and dates.

parboot(td, nreps = 100, ncpu = 1, overrideTempConstraint = TRUE,
  overrideClock = NULL, overrideSearchRoot = TRUE,
  overrideSeqLength = NULL, quiet = TRUE, normalApproxTMRCA = FALSE,
  parallel_foreach = FALSE)

`td`	A fitted treedater object
`nreps`	Integer number of simulations to be carried out
`ncpu`	Number of threads to use for parallel computation. Recommended.
`overrideTempConstraint`	If TRUE (default) will not enforce positive branch lengths in simualtion replicates. Will speed up execution.
`overrideClock`	May be 'strict' or 'additive' or 'uncorrelated' in which case will force simulations to fit the corresponding model. If ommitted, will inherit the clock model from td
`overrideSearchRoot`	If TRUE, will re-use root position from input treedater tree. Otherwise may re-estimate root position in simulations
`overrideSeqLength`	Optional sequence length to use in simulations
`quiet`	If TRUE will minimize output printed to screen
`normalApproxTMRCA`	If TRUE will use estimate standard deviation from simulation replicates and report confidence interval based on normal distribution
`parallel_foreach`	If TRUE will use the foreach package for parallelization. May work better on HPC systems.

If the original treedater fit estimated the root position, root position will also be estimated for each simulation, so the returned trees may have different root positions. Some replicates may converge to a strict clock or a relaxed clock, so the parameter estimates in each replicate may not be directly comparable. It is possible to compute confidence intervals for the times of particular nodes or for estimated sample times by inspecting the output from each fitted treedater object, which is contained in the $trees attribute.

A list with elements

trees: The fitted treedater objects corresponding to each simulation
meanRates: Vector of estimated rates for each simulation
meanRate_CI: Confidence interval for substitution rate
coef_of_variation_CI: Confidence interval for rate variation
timeOfMRCA_CI: Confidence interval for time of common ancestor

Erik M Volz <erik.volz@gmail.com>

dater boot

# make a random tree
tre <- ape::rtree(25)
# simulate sample times based on distance from root to tip:
sts <- setNames( ape::node.depth.edgelength( tre )[1:ape::Ntip(tre)], tre$tip.label)
# modify edge length to represent evolutionary distance with rate 1e-3:
tre$edge.length <- tre$edge.length * 1e-3
# treedater: 
td <- dater( tre, sts=sts, s=1000, clock='strict', omega0=.0015 )
# parametric bootstrap: 
pb <- parboot( td, nreps=25 )
# plot lineages through time
plot( pb )