Control Values for fit_ssm. — ssm

ssm_control selects the numerical minimizer, method, associated control parameters, and parameter bounds used by fit_ssm.

ssm_control(
  optim = c("nlminb", "optim"),
  method = c("L-BFGS-B", "BFGS", "Nelder-Mead", "CG", "SANN", "Brent"),
  lower = NULL,
  upper = NULL,
  verbose = 1,
  se = FALSE,
  ...
)

Arguments

optim: the numerical optimizer used in the fit
method: if optim = "optim" then the optimization method to be used can be one of "BFGS", "L-BFGS-B", "Nelder-Mead", "CG", "SANN", or "Brent" see optim for details
lower: a list named parameter lower bounds, if NULL then built in defaults are used when method = "L-BFGS-B". Possible parameter names are: l_sigma a vector of length 2, log scale; l_rho_p a scalar, logit scale; l_D a scalar, log scale; l_psi a scalar, log scale; l_tau a vector of length 2, log scale; l_rho_o a scalar, logit scale
upper: a list of named parameter upper bounds, if NULL then built in defaults are used when method = "L-BFGS-B". Possible parameter names are same as lower
verbose: integer; report progress during minimization: 0 = silent; 1 = parameter trace (default); 2 = optimizer trace
se: logical; should standard errors for speed estimates be calculated (default = FALSE). Turning this on will slow down computation time but provide SE's for speed-along-track calculations
...: control parameters for the chosen optimizer

Value

Returns a list with components

optim: the name of the numerical optimizer as a string, "nlminb" or "optim"
method: optimization method to be used
lower: named list of lower parameter bounds
upper: named list of upper parameter bounds
verbose: level of tracing information to be reported
control: list of control parameters for the optimizer

Details

The optimizer used to minimize the objective function is selected by the optim argument. Additional control parameters specific to the chosen optimizer are specified via the dots argument. See nlminb and optim for available options. Adapted from S. Wotherspoon https://github.com/SWotherspoon/RWalc/blob/master/R/RWalc.R

Examples

fit <- fit_ssm(ellie,
vmax = 4,
model = "crw",
time.step = 72,
control = ssm_control(
    optim = "nlminb",
    eval.max = 2000)
    )
#> fitting crw SSM to 1 tracks...
#> 
 pars:   1 1 0 -3.35398      
 pars:   0.39011 0.36995 -0.01715 -3.83437      
 pars:   -1.43958 -1.5202 -0.06862 -5.27553      
 pars:   -2.32555 -2.54729 -0.19371 -4.12372      
 pars:   -0.8182 -0.89535 -0.06643 -4.50381      
 pars:   -1.32518 -1.50336 -0.13293 -2.80663      
 pars:   -2.70765 -2.68894 -0.23564 -2.37746      
 pars:   -3.27563 -3.39761 -0.40156 -0.74674      
 pars:   -4.54561 -2.25375 -0.86806 -0.13627      
 pars:   -3.3297 -3.27793 -0.43777 -0.61077      
 pars:   -3.36938 -3.29518 -0.51676 -0.44068      
 pars:   -3.37129 -3.28379 -0.68713 -0.35188      
 pars:   -3.37129 -3.28379 -0.68713 -0.35188

Control Values for `fit_ssm`.

Arguments

Value

Details

See also

Examples