sim.OU: Simulate an Ornstein-Uhlenbeck time-series

In paleoTS: Analyze Paleontological Time-Series

Simulate an Ornstein-Uhlenbeck time-series

Description

Simulate an Ornstein-Uhlenbeck time-series

Usage

sim.OU(
  ns = 20,
  anc = 0,
  theta = 10,
  alpha = 0.3,
  vstep = 0.1,
  vp = 1,
  nn = rep(20, ns),
  tt = 0:(ns - 1)
)

Arguments

ns	number of populations in the sequence
anc	ancestral phenotype
theta	OU optimum (long-term mean)
alpha	strength of attraction to the optimum
vstep	step variance
vp	phenotypic variance of each sample
nn	vector of sample sizes
tt	vector of sample times (ages)

Details

This function simulates an Ornstein-Uhlenbeck (OU) process. In microevolutionary terms, this models a population ascending a nearby peak in the adaptive landscape. The optimal trait value is theta, alpha indicates the strength of attraction to that peak (= strength of stabilizing selection around theta), vstep measures the random walk component (from genetic drift) and anc is the trait value at the start of the sequence.

Value

a paleoTS object

References

Hunt, G., M. A. Bell and M. P. Travis. 2008. Evolution toward a new adaptive optimum: phenotypic evolution in a fossil stickleback lineage. Evolution 62(3): 700-710.

See Also

opt.joint.OU

Examples

x1 <- sim.OU(alpha = 0.8)  # strong alpha
x2 <- sim.OU(alpha = 0.1)  # wearker alpha
plot(x1)
plot(x2, add = TRUE, col = "blue")

paleoTS documentation built on Aug. 9, 2022, 1:06 a.m.