fitMult | R Documentation |
Fit the same simple model across multiple time-series
fitMult( yl, model = c("GRW", "URW", "Stasis", "covTrack"), method = c("Joint", "AD"), pool = TRUE, zl = NULL, hess = FALSE )
yl |
a list of |
model |
the model to fit; see Details |
method |
parameterization to use: |
pool |
if TRUE, sample variances are substituted with their pooled estimate |
zl |
for the |
hess |
if TRUE, standard errors computed from the Hessian matrix are returned |
This function fits a model with shared parameters across multiple trait time-series. The most likely application would be to model a common evolutionary dynamic across different sequences, perhaps representing time-series of the same trait and lineage from different localities or time intervals.
Four simple models are currently implemented:
GRW:
parameters mstep
and vstep
of the general random walk are
shared across sequences.
URW: parameter vstep
of the
unbiased random walk is shared across sequences.
Stasis:
parameter omega
of stasis is shared across sequences.
covTrack: parameters b0
, b1
, and evar
of the
covariate-tracking model are shared across sequences.
Under the joint parameterization, method = "Joint"
, an additional parameter, anc
is
fit, representing the ancestral (starting) trait value. This parameter is estimated separately
in each sequence so it is not assumed that they all start at the same trait value.
a paleoTSfit
object with the results of the model-fitting
The models are described in the help for fitSimple
and the functions
linked from there.
fitSimple
x1 <- sim.GRW(ms = 1, vs = 0.2) x2 <- sim.GRW(ms = 1, vs = 0.2) fitMult(list(x1, x2), model = "GRW")
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