Continuous Character Simulation
This function simulates the evolution of a continuous character along a phylogeny. The calculation is done recursively from the root. See Paradis (2012, pp. 232 and 324) for an introduction.
rTraitCont(phy, model = "BM", sigma = 0.1, alpha = 1, theta = 0, ancestor = FALSE, root.value = 0, ...)
phy |
an object of class |
model |
a character (either |
sigma |
a numeric vector giving the standard-deviation of the random component for each branch (can be a single value). |
alpha |
if |
theta |
if |
ancestor |
a logical value specifying whether to return the values at the nodes as well (by default, only the values at the tips are returned). |
root.value |
a numeric giving the value at the root. |
... |
further arguments passed to |
There are three possibilities to specify model
:
"BM"
:a Browian motion model is used. If the arguments
sigma
has more than one value, its length must be equal to the
the branches of the tree. This allows to specify a model with variable
rates of evolution. You must be careful that branch numbering is done
with the tree in “postorder” order: to see the order of the branches
you can use: tr <- reorder(tr, "po"); plor(tr); edgelabels()
.
The arguments alpha
and theta
are ignored.
"OU"
:an Ornstein-Uhlenbeck model is used. The above
indexing rule is used for the three parameters sigma
,
alpha
, and theta
. This may be interesting for the last
one to model varying phenotypic optima. The exact updating formula
from Gillespie (1996) are used which are reduced to BM formula if
alpha = 0
.
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. The arguments
sigma
, alpha
, and theta
are ignored.
A numeric vector with names taken from the tip labels of
phy
. If ancestor = TRUE
, the node labels are used if
present, otherwise, “Node1”, “Node2”, etc.
Emmanuel Paradis
Gillespie, D. T. (1996) Exact numerical simulation of the Ornstein-Uhlenbeck process and its integral. Physical Review E, 54, 2084–2091.
Paradis, E. (2012) Analysis of Phylogenetics and Evolution with R (Second Edition). New York: Springer.
data(bird.orders) rTraitCont(bird.orders) # BM with sigma = 0.1 ### OU model with two optima: tr <- reorder(bird.orders, "postorder") plot(tr) edgelabels() theta <- rep(0, Nedge(tr)) theta[c(1:4, 15:16, 23:24)] <- 2 ## sensitive to 'alpha' and 'sigma': rTraitCont(tr, "OU", theta = theta, alpha=.1, sigma=.01) ### an imaginary model with stasis 0.5 time unit after a node, then ### BM evolution with sigma = 0.1: foo <- function(x, l) { if (l <= 0.5) return(x) x + (l - 0.5)*rnorm(1, 0, 0.1) } tr <- rcoal(20, br = runif) rTraitCont(tr, foo, ancestor = TRUE) ### a cumulative Poisson process: bar <- function(x, l) x + rpois(1, l) (x <- rTraitCont(tr, bar, ancestor = TRUE)) plot(tr, show.tip.label = FALSE) Y <- x[1:20] A <- x[-(1:20)] nodelabels(A) tiplabels(Y)
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