# rTraitDisc

From ape v2.7-3
0th

Percentile

##### Discrete Character Simulation

This function simulates the evolution of a discrete character along a phylogeny. If model is a character or a matrix, evolution is simulated with a Markovian model; the transition probabilities are calculated for each branch with $P = e^{Qt}$ where $Q$ is the rate matrix given by model and $t$ is the branch length. The calculation is done recursively from the root. See Paradis (2006, p. 101) for a general introduction applied to evolution.

Keywords
datagen
##### Usage
rTraitDisc(phy, model = "ER", k = if (is.matrix(model)) ncol(model) else 2,
rate = 0.1, states = LETTERS[1:k], freq = rep(1/k, k),
ancestor = FALSE, root.value = 1, ...)
##### Details

There are three possibilities to specify model:

• A matrix:
{it must be a numeric square matrix; the diagonal is always ignored. The arguments k and rate are ignored.}

A character:{these are the same short-cuts than in the function ace: "ER" is an equal-rates model, "ARD" is an all-rates-different model, and "SYM" is a symmetrical model. Note that the argument rate must be of the appropriate length, i.e., 1, $k(k - 1)$, or $k(k - 1)/2$ for the three models, respectively. The rate matrix $Q$ is then filled column-wise.}

A function:{it must be of the form foo(x, l) where x is the trait of the ancestor and l is the branch length. It must return the value of the descendant as an integer.}

##### Value

A factor with names taken from the tip labels of phy. If ancestor = TRUE, the node labels are used if present, otherwise, Node1'', Node2'', etc.

##### References

Paradis, E. (2006) Analyses of Phylogenetics and Evolution with R. New York: Springer.

rTraitCont, rTraitMult, ace

##### Examples
data(bird.orders)
### the two followings are the same:
rTraitDisc(bird.orders)
rTraitDisc(bird.orders, model = matrix(c(0, 0.1, 0.1, 0), 2))
### two-state model with irreversibility:
rTraitDisc(bird.orders, model = matrix(c(0, 0, 0.1, 0), 2))
### an imaginary model with stasis 0.5 time unit after a node, then
### random evolution:
foo <- function(x, l) {
if (l < 0.5) return(x)
sample(2, size = 1)
}
tr <- rcoal(20, br = runif)
x <- rTraitDisc(tr, foo, ancestor = TRUE)
plot(tr, show.tip.label = FALSE)
co <- c("blue", "yellow")
cot <- c("white", "black")
Y <- x[1:20]
A <- x[-(1:20)]
nodelabels(A, bg = co[A], col = cot[A])
tiplabels(Y, bg = co[Y], col = cot[Y])
Documentation reproduced from package ape, version 2.7-3, License: GPL (>= 2)

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