logL.GRW {paleoTS} | R Documentation |
Returns log-likelihood for general random walk logL.GRW
, unbiased random walk logL.URW
, and stasis logL.Stasis
models.
logL.GRW(p, y) logL.URW(p, y) logL.Stasis(p, y)
p |
vector of parameters |
y |
a paleoTS object |
For the general random walk, p = c(mstep, vstep)
; for an unbiased random walk, p = vstep
; for the stasis model, p = c(theta, omega)
. In general, users will not be access these functions directly, but instead use the optimization functions, which use these functions to find the best-supported parameter values.
The log-likelihood of the parameter estimates (p
), given the data (y
).
Gene Hunt
Hunt, G. 2006. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology32:578–601.
y<- sim.GRW(20, 0, 1) L1 <- logL.GRW(p=c(0,1), y) # actual parameters L2 <- logL.GRW(p=c(10,10), y) # should be a bad guess cat (L1, L2, "\n")