logL.RW {paleoTS} | R Documentation |
Returns log-likelihood for general random walk logL.RW
, unbiased random walk logL.RWu
, and stasis logL.stasis
models.
logL.RW(p, y, pool = TRUE) logL.RWu(p, y, pool = TRUE) logL.stasis(p, y, pool = TRUE)
p |
vector of parameters |
y |
a paleoTS object |
pool |
logical, if TRUE, variances are pooled across samples |
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. 2007. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology32:578–601.
y<- sim.rw(20, 0, 1) L1 <- logL.RW(p=c(0,1), y) # actual parameters L2 <- logL.RW(p=c(10,10), y) # should be a bad guess cat (L1, L2, "\n")