optimize_RTMB: Optimize RTMB model

In multiSA: Multi-Stock Assessment

Optimize RTMB model

Description

A convenient function that fits a RTMB model and calculates standard errors.

Usage

optimize_RTMB(
  obj,
  hessian = FALSE,
  restart = 0,
  do_sd = TRUE,
  control = list(iter.max = 2e+05, eval.max = 4e+05),
  lower = -Inf,
  upper = Inf,
  silent = FALSE
)

Arguments

obj	The list returned by RTMB::MakeADFun()
hessian	Logical, whether to pass the Hessian function obj$he to stats::nlminb(). Only used if there are no random effects in the model.
restart	Integer, the maximum number of additional attempts to fit the model. See details.
do_sd	Logical, whether to calculate standard errors through get_sdreport()
control	List of options passed to stats::nlminb()
lower	Lower bounds of parameters passed to stats::nlminb()
upper	Upper bounds of parameters passed to stats::nlminb()
silent	Logical, whether to report progress to console

Details

Argument restart allows for recursive model fitting to obtain convergence, through the following procedure:

1. Optimize model with stats::nlminb().

2. Determine convergence, defined by RTMB::sdreport() by whether the Cholesky decomposition of the covariance matrix is possible.

3. If convergence is not achieved, jitter parameter estimates with multiplicative factor rlnorm(mean = 0, sd = 1e-3) and return to step 1.

Value

A named list: "opt" is the output of stats::nlminb() and "SD" is the output of get_sdreport()

See Also

get_sdreport()

multiSA documentation built on March 21, 2026, 1:06 a.m.