Builds the TMB ADFun object for a multi-map disaggregation model, then fits the model by maximizing the TMB objective and approximates uncertainty via the optimized Hessian.
Usage
disag_model_mmap_tmb(
data,
priors = NULL,
family = "poisson",
link = "log",
time_varying_betas = FALSE,
fixed_effect_betas = TRUE,
iterations = 1000,
field = TRUE,
iid = TRUE,
hess_control_parscale = NULL,
hess_control_ndeps = 1e-04,
silent = TRUE,
starting_values = NULL,
verbose = FALSE
)Arguments
- data
A 'disag_data_mmap' object (from 'prepare_data_mmap()').
- priors
Optional named list of prior specifications (see internal helper).
- family
One of 'gaussian', 'binomial', 'poisson', or 'negbinomial'.
- link
One of 'identity', 'logit', or 'log'.
- time_varying_betas
Logical; if TRUE, each time point has its own fixed-effect
- fixed_effect_betas
Logical; if TRUE (default), active beta coefficients are treated as fixed effects. If FALSE, active beta coefficients are treated as random effects in the inner Laplace step.
- iterations
Integer >= 1: maximum number of optimizer iterations.
- field
Logical: include the spatial random field?
- iid
Logical: include polygon-specific IID effects?
- hess_control_parscale
Optional numeric vector for scaling the Hessian steps.
- hess_control_ndeps
Numeric; relative step size for Hessian finite-difference (default 1e-4).
- silent
Logical: if TRUE, suppress TMB's console output.
- starting_values
Optional named list of starting parameter values.
- verbose
Logical: if TRUE, print total runtime.