| tess.sim.age | R Documentation | 
tess.sim.age simulates a reconstructed phylogenetic tree under a global, time-dependent birth-death process conditioned on the age of the tree. The rates may be any positive function of time or a constant. The process starts at time 0 and goes forward in time, hence the rates and events should be interpreted in the time after the origin. Additionally, mass-extinction event can be provided and a uniform taxon sampling probability. It is possible to start either with the origin (1 species) or with the most recent common ancestor (2 species).
tess.sim.age(n, age, lambda, mu, massExtinctionTimes = c(), massExtinctionSurvivalProbabilities = c(), samplingProbability = 1, samplingStrategy = "uniform", maxTaxa = Inf, MRCA = TRUE)
| n | Number of simulations. | 
| age | The age of the tree, i.e. the time to simulate. | 
| lambda | The speciation rate function or constant. | 
| mu | The extinction rate function or constant. | 
| massExtinctionTimes | The set of mass-extinction times after the start of the process. | 
| massExtinctionSurvivalProbabilities | The set of survival probabilities for each speciation event. The set must have the same length as the set of mass-extinction times. | 
| samplingProbability | The probability for a species to be included in the sample. | 
| samplingStrategy | The strategy how samples were obtained. Options are: uniform|diversified. | 
| maxTaxa | The maximum number of possible taxa. If by chance a higher number is simulated, than simply ntaxa=maxTaxa. This is useful when too large trees should be simulated because this takes too much time and memory. | 
| MRCA | Does the process start with the most recent common ancestor? | 
Returns a set of trees in 'phylo' format.
Sebastian Hoehna
S. Hoehna: Fast simulation of reconstructed phylogenies under global, time-dependent birth-death processes. 2013, Bioinformatics, 29:1367-1374
l <- Vectorize(function(x) { if (x > 0.5 || x < 0.3) { return (1) } else { return (2) } })
e <- Vectorize(function(x) { if (x > 0.5 || x < 0.3) { return (0.95) } else { return (0.5) } })
tess.sim.age(n=1,age=1,l,e,MRCA=TRUE)
# simulation under constant rates
tess.sim.age(n=1,age=1,2.0,1.0,MRCA=TRUE)
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