powered by
Function to find maximum likelihood solutions to a Unbiased Random Walk with an decelerating or decelerating rate of change through time.
opt.joint.decel(y, pool = TRUE, meth = "L-BFGS-B", hess = FALSE)
the log-likelihood of the optimal solution
AIC with a correction for small sample sizes
parameter estimates
abbreviated model name
Joint consideration of all samples
number of parameters in the model
the number of observations/samples
an univariate evoTS object.
logical indicating whether to pool variances across samples
optimization method, passed to function optim. Default is "L-BFGS-B".
logical, indicating whether to calculate standard errors from the Hessian matrix.
Kjetil Lysne Voje
Voje, K. L. 2020. Testing eco‐evolutionary predictions using fossil data: Phyletic evolution following ecological opportunity.Evolution 74:188–200.
## Generate a paleoTS object by simulating a univariate evolutionary sequence x <- paleoTS::sim.GRW(30) ## Fit the model opt.joint.decel(x)
Run the code above in your browser using DataLab