sim.GRW.shift: Simulate (general) random walk with shift(s) in generating...

In paleoTS: Analyze Paleontological Time-Series

Simulate (general) random walk with shift(s) in generating parameters

Description

Simulate (general) random walk with shift(s) in generating parameters

Usage

sim.GRW.shift(
  ns = c(10, 10),
  ms = c(0, 1),
  vs = c(0.5, 0.5),
  nn = rep(30, sum(ns)),
  tt = 0:(sum(ns) - 1),
  vp = 1
)

Arguments

ns	vector of the number of samples in each segment
ms	vector of mean step parameter in each segment
vs	vector of step variance parameter in each segment
nn	vector of sample sizes, one for each population
tt	vector of samples times (ages)
vp	phenotypic variance in each sample

Details

Simulates under a model in which a sequence is divided into two or more segments. Trait evolution proceeds as a general random walk, with each segment getting its own generating parameters (mstep, vstep).

Value

a paleoTS object with the simulated time-series

See Also

sim.GRW, sim.sgs, opt.GRW.shift

Examples

x <- sim.GRW.shift(ns = c(10,10,10), ms = c(0, 1, 0), vs = c(0.1,0.1,0.1))
plot(x)
abline(v = c(9.5, 19.5), lty = 3, lwd = 2, col = "blue")  # shows where dynamics shift
text (c(5, 15, 25), c(2,2,2), paste("segement", 1:3, sep =" "), col = "blue")

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