sim.covTrack | R Documentation |

Simulate trait evolution that tracks a covariate

sim.covTrack( ns = 20, b = 1, evar = 0.1, z, nn = rep(20, times = ns), tt = 0:(ns - 1), vp = 1 )

`ns` |
number of populations in a sequence |

`b` |
slope of the relationship between the change in the covariate and the change in the trait |

`evar` |
residual variance of the same relationship |

`z` |
vector of covariate that the trait tracks |

`nn` |
vector of sample sizes for populations |

`tt` |
vector of times (ages) for populations |

`vp` |
phenotypic trait variance within each population |

In this model, changes in a trait are linearly related to changes in
a covariate with a slope of `b`

and residual variance `evar`

:
`dx = b * dz + eps`

, where `eps ~ N(0, evar)`

. This model was
described, and applied to an example in which body size changes tracked
changes in temperature, by Hunt et al. (2010).

a `paleoTS`

object

For a trait sequence of length `ns`

, the covariate, `z`

, can
be of length `ns`

- 1,in which case it is interpreted as the vector of
*changes*, `dz`

. If `z`

is of length `ns`

,
differences are taken and these are used as the `dz`

's.

Hunt, G, S. Wicaksono, J. E. Brown, and K. G. Macleod. 2010.
Climate-driven body size trends in the ostracod fauna of the deep Indian
Ocean. *Palaeontology* 53(6): 1255-1268.

set.seed(13) z <- c(1, 2, 2, 4, 0, 8, 2, 3, 1, 9, 4, 3) x <- sim.covTrack(ns = 12, z = z, b = 0.5, evar = 0.2) plot(x, ylim = c(-1, 10)) lines(x$tt, z, col = "blue")

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