mle.rw {paleoTS} | R Documentation |
These functions calculate maximum likelihood estimators for the general random walk (mle.rw
) and stasis (mle.stasis
) models.
mle.rw(x) mle.stasis(x)
x |
a paleoTS object |
These functions return maximum likelihood estimators for the general random walk mle.rw
and stasis mle.stasis
models, but only under a restriced set of circumstances are these valid!. For these estimators to be valid, the sampling error must be the same in all samples, which generally means equal sample size and variances in all samples. For the general random walk model, it is also assumed that samples are evenly spaced in time. Because these assumptions usually do not hold for paleontological data, almost all users should instead use the numerical optimization functions (see opt.RW
). The main purpose for the present functions is to provide starting estimates for numerical optimization.
a vector of parameter estimates, either c(mstep, vstep)
, or c(theta, omega)
Gene Hunt
Hunt, G. 2007. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology, in press.
## Warning: better to use opt.RW() for real data y <- sim.rw(ns=20, 0, 1) w <- mle.rw(y)