sim.OU {paleoTS}R Documentation

Simulate evolutionary time-series

Description

Generates an evolutionary time-series according to an Orstein-Uhlenbeck (OU) model.

Usage

sim.OU(ns = 20, anc = 0, theta = 10, alpha = 0.3, vs = 0.1, vp = 1, nn = rep(20, ns), tt = 1:ns)
ou.M(anc, theta, aa, tt)
ou.V(vs, aa, tt)

Arguments

ns number of samples in time-series
anc ancestral phenotype at the start of the series
theta phenotype of the evolutionary optimum
alpha strength of the attracting force pulling the population to the optimum
vs step variance of the random walk component of change
vp within-population trait variance
nn vector of the number of individuals in each sample
tt vector of sample ages, increases from oldest to youngest
aa strength of the attracting force pulling the population to the optimum (same as alpha)

Details

See Hansen (1997) for a description of this model in a macroevolutionary context. This model also arises naturally in microevolution as a finite population evolving in the vicinity of an optimum in the adaptive landscape; see Lande (1976) and Estes & Arnold (2007).
Functions ou.M and ou.V are used internally by sim.OU and add.OU.curves to generate the means and variances of an OU process.

Value

A paleoTS object for sim.OU. For ou.M and ou.V, a vector of means or variances, respectively, are generated.

Author(s)

Gene Hunt

References

Lande, R. 1976. Natural selection and random genetic drift in phenotypic evolution. Evolution 30:314-334.
Hansen, T. 1997. Stabilizing selection and the comparative analysis of adaptation. Evolution 51:1341-1351.
Estes, S. & Arnold, S. J. 2007. Resolving the paradox of stasis: models of stabilizing selection explain evolutionary divergence on all timescales. American Naturalist 169:227-244.
Hunt, G., M. Bell & M. Travis. 2008. Evolution towards a new adaptive optimum: phenotypic evolution in a fossil stickleback lineage. Evolution in press.

See Also

sim.GRW, opt.joint.OU

Examples

x1<- sim.OU(ns=100, anc=0, theta=10, alpha=0.2, vs=0.1, vp=0.1, nn=rep(100, times=100), tt=0:99)
plot(x1)

[Package paleoTS version 0.3-1 Index]