Function to run TMB to estimate track

Function to run TMB to estimate track

runYaps(
  inp,
  maxIter = 1000,
  getPlsd = TRUE,
  getRep = TRUE,
  silent = TRUE,
  opt_fun = "nlminb",
  opt_controls = list(),
  bounds = list()
)

runTmb(
  inp,
  maxIter = 1000,
  getPlsd = TRUE,
  getRep = TRUE,
  silent = TRUE,
  opt_fun = "nlminb",
  opt_controls = list(),
  bounds = list()
)

Arguments

inp	inp-object obtained from getInp()
maxIter	Sets inner.control(maxit) of the tmb-call. Increase if model is not converging.
getPlsd, getRep	Whether or not to get sd estimates (plsd=TRUE) and reported values (getRep=TRUE).
silent	Logical whether to keep the optimization quiet.
opt_fun	Which optimization function to use. Default is 'nlminb' - alternative is 'nloptr' (experimental!). If using 'nloptr', `opt_controls` must be specified.
opt_controls	List of controls passed to optimization function. For instances, tolerances such as x.tol=1E-8. If opt_fun = 'nloptr', `opt_controls` must be a list formatted appropriately. For instance: opt_controls <- list(algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) ). See `?nloptr` and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in `nloptr` require bounded parameters - see `bounds`.
bounds	List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) ).