fit.sgs: Fit a model of trait evolution with a protracted punctuation.

In paleoTS: Analyze Paleontological Time-Series

Fit a model of trait evolution with a protracted punctuation.

Description

This function fits a model of punctuated change that is is protracted enough that it is captured by multiple transitional populations. Trait evolution starts in stasis, shifts to a general random walk, and then shifts back into stasis.

Usage

fit.sgs(
  y,
  minb = 7,
  oshare = TRUE,
  pool = TRUE,
  silent = FALSE,
  hess = FALSE,
  meth = "L-BFGS-B",
  model = "GRW"
)

Arguments

y	a paleoTS object
minb	minimum number of populations within each segment
oshare	logical, if TRUE, variance assumed to be shared (equal) across segments
pool	if TRUE, sample variances are substituted with their pooled estimate
silent	logical, if TRUE, progress updates are suppressed
hess	if TRUE, standard errors computed from the Hessian matrix are returned
meth	optimization method, passes to optim
model	type of random walk: "URW", unbiased random walk, or "GRW", a general (directional) random walk

Value

a paleoTSfit object

See Also

fitGpunc

Examples

## Not run: 
x <- sim.sgs(ns = c(15, 15, 15))  # default values OK
w <- fit.sgs(x, minb = 10)  # increase minb so example takes less time; not recommended!
plot(x)
abline(v = c(16, 31), lwd = 3)  # actual shifts
abline(v = c(w$parameters[6:7]), lwd = 2, lty = 3, col = "red")  # inferred shifts

## End(Not run)

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