TESS-package            Fast simulation of reconstructed phylogenetic
                        trees under time-dependent birth-death
                        processes
cettiidae               Cettiidae phylogeny from Alstroem et al. (2011)
globalBiDe.likelihood   globalBiDe.likelihood: Probability density of a
                        tree under a global, time-dependent birth-death
                        process
globalBiDe.nTaxa.expected
                        globalBiDe.nTaxa.expected: The expected number
                        of taxa at present of a tree under a global,
                        time-dependent birth-death process (E[N(T)])
mammalia                Dated family level mammalian phylogeny from
                        Meredith et al. (2011): Impacts of the
                        cretaceous terrestrial revolution and kpg
                        extinction on mammal diversification.
sim.globalBiDe.age      sim.globalBiDe.age: Simulate a reconstructed
                        tree for a given age under a global,
                        time-dependent birth-death process.
sim.globalBiDe.taxa     sim.globalBiDe.taxa.taxa: Simulate a
                        reconstructed tree for a given number of taxa
                        under a global, time-dependent birth-death
                        process.
sim.globalBiDe.taxa.age
                        sim.globalBiDe.taxa.taxa.age: Simulate a
                        reconstructed tree for a given age and number
                        of taxa under a global, time-dependent
                        birth-death process.
tess.PosteriorPrediction
                        tess.PosteriorPrediction: Approximation of the
                        posterior predictive distribution.
tess.PosteriorPredictiveTest
                        tess.PosteriorPredictiveTest: Approximation of
                        the posterior predictive distribution.
tess.mcmc               tess.mcmc: Metropolis-Hastings algorithm.
tess.steppingStoneSampling
                        tess.steppingStoneSampling: Marginal likelihood
                        estimation via Stepping-Stone-Sampling.
