Learn R Programming

TESS (version 2.1.2)

Diversification Rate Estimation and Fast Simulation of Reconstructed Phylogenetic Trees under Tree-Wide Time-Heterogeneous Birth-Death Processes Including Mass-Extinction Events

Description

Simulation of reconstructed phylogenetic trees under tree-wide time-heterogeneous birth-death processes and estimation of diversification parameters under the same model. Speciation and extinction rates can be any function of time and mass-extinction events at specific times can be provided. Trees can be simulated either conditioned on the number of species, the time of the process, or both. Additionally, the likelihood equations are implemented for convenience and can be used for Maximum Likelihood (ML) estimation and Bayesian inference.

Copy Link

Version

Install

install.packages('TESS')

Monthly Downloads

406

Version

2.1.2

License

GPL-3

Maintainer

Sebastian Hoehna

Last Published

April 25th, 2022

Functions in TESS (2.1.2)

tess.PosteriorPredictiveTest

tess.PosteriorPredictiveTest: Approximation of the posterior predictive distribution.
tess.plot.output

tess.plot.output: Plotting the output of a diversification rate estimation including mass-extinction events.
conifers

Conifer phylogeny from Leslie et al. (2012)
mammalia

Dated family level mammalian phylogeny from Meredith et al. (2011): Impacts of the cretaceous terrestrial revolution and kpg extinction on mammal diversification.
TESS-package

Diversification rate estimation and fast simulation of reconstructed phylogenetic trees under tree-wide time-heterogeneous birth-death processes including mass-extinction events
cettiidae

Cettiidae phylogeny from Alstroem et al. (2011)
tess.sim.taxa.age

tess.sim.taxa.taxa.age: Simulate a reconstructed tree for a given age and number of taxa under a global, time-dependent birth-death process.
tess.nTaxa.expected

tess.nTaxa.expected: The expected number of taxa at present of a tree under a global, time-dependent birth-death process ( E[ N(T) ] )
tess.mcmc

tess.mcmc: Markov chain Monte Carlo simulation using a general Metropolis-Hastings algorithm.
tess.likelihood.rateshift

tess.likelihood.rateshift: Probability density of a tree under a tree-wide time-dependent birth-death-shift process
tess.pathSampling

tess.pathSampling: Marginal likelihood estimation via Path-Sampling.
tess.sim.taxa

tess.sim.taxa.taxa: Simulate a reconstructed tree for a given number of taxa under a global, time-dependent birth-death process.
tess.sim.age

tess.sim.age: Simulate a reconstructed tree for a given age under a global, time-dependent birth-death process.
tess.likelihood

tess.likelihood: Probability density of a tree under a tree-wide time-dependent birth-death process
tess.steppingStoneSampling

tess.steppingStoneSampling: Marginal likelihood estimation via Stepping-Stone-Sampling.
tess.process.output

tess.process.output: Summarizing the output of a diversification rate estimation including mass-extinction events. See the tess.analysis function for more information on how such output is generated and the tess.plot.output how the output can be visualized. Also have a look at the vignette for more in detail description and examples.
tess.plot.singlechain.diagnostics

tess.plot.mcmc.diagnostics: Plotting the single chain mcmc diagnostics of a episodic diversification rate analysis with mass-extinction events.
tess.analysis

tess.analysis: Diversification rate estimation under an episodic birth-death process including mass-extinction events.
tess.plot.multichain.diagnostics

tess.plot.multichain.diagnostics: Plotting the mcmc diagnostics of a episodic diversification rate analysis with mass-extinction events.
tess.PosteriorPrediction

tess.PosteriorPrediction: Approximation of the posterior predictive distribution.