opt.joint.OU | R Documentation |
Fit Ornstein-Uhlenbeck model using the "Joint" parameterization
opt.joint.OU(
y,
pool = TRUE,
cl = list(fnscale = -1),
meth = "L-BFGS-B",
hess = FALSE
)
y |
a |
pool |
if TRUE, sample variances are substituted with their pooled estimate |
cl |
optional control list, passed to |
meth |
optimization algorithm, passed to |
hess |
if TRUE, return standard errors of parameter estimates from the hessian matrix |
This function fits an Ornstein-Uhlenbeck (OU) model to time-series data. The OU
model has four generating parameters: an ancestral trait value (anc
), an optimum
value (theta
), the strength of attraction to the optimum (alpha
), and a
parameter that reflects the tendency of traits to diffuse (vstep
). In a
microevolutionary context, these parameters can be related to natural selection and
genetic drift; see Hunt et al. (2008).
a paleoTSfit
object with the model fitting results
It is easier to use the convenience function fitSimple
. Note also that
preliminary work found that the "AD" parameterization did not perform as well for the OU
model and thus it is not implemented here.
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.
fitSimple
, opt.joint.GRW
x <- sim.OU(vs = 0.5) # most defaults OK
w <- opt.joint.OU(x)
plot(x, modelFit = w)
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