Fit a FIMS model (BETA)
Usage
fit_fims(
input,
get_sd = TRUE,
save_sd = TRUE,
number_of_loops = 3,
optimize = TRUE,
number_of_newton_steps = 0,
control = list(eval.max = 10000, iter.max = 10000, trace = 0),
filename = NULL,
getReportCovariance = FALSE
)Arguments
- input
Input list as returned by
initialize_fims().- get_sd
A boolean specifying if the
TMB::sdreport()should be calculated?- save_sd
A logical, with the default
TRUE, indicating whether the sdreport is returned in the output. IfFALSE, the slot for the report will be empty.- number_of_loops
A positive integer specifying the number of iterations of the optimizer that will be performed to improve the gradient. The default is three, leading to four total optimization steps.
- optimize
Optimize (TRUE, default) or (FALSE) build and return a list containing the obj and report slot.
- number_of_newton_steps
The number of Newton steps using the inverse Hessian to do after optimization. Not yet implemented.
- control
A list of optimizer settings passed to
stats::nlminb(). The the default is a list of length three witheval.max = 1000,iter.max = 10000, andtrace = 0.- filename
Character string giving a file name to save the fitted object as an RDS object. Defaults to 'fit.RDS', and a value of NULL indicates not to save it. If specified, it must end in .RDS. The file is written to folder given by
input[["path"]]. Not yet implemented.- getReportCovariance
A logical passed to
TMB::sdreport(), with the defaultFALSE. Standard errors of all parameters and derived quantities are calculated either way. IfTRUE, the full covariance matrix of the derived quantities is also calculated and stored ascovin thesdreport; it grows with the square of the number of derived quantities and can use several GB of memory. IfFALSE,covisNA.
Value
An object of class FIMSFit is returned, where the structure is the same
regardless if optimize = TRUE or not. Uncertainty information is only
included in the estimates slot if get_sd = TRUE.
