fit.bage_mod: Fit a Model

In bage: Bayesian Estimation and Forecasting of Age-Specific Rates

Fit a Model

Description

Calculate the posterior distribution for a model.

Usage

## S3 method for class 'bage_mod'
fit(
  object,
  method = c("standard", "inner-outer"),
  vars_inner = NULL,
  optimizer = c("multi", "nlminb", "BFGS", "CG"),
  quiet = TRUE,
  start_oldpar = FALSE,
  ...
)

Arguments

object	A bage_mod object, created with mod_pois(), mod_binom(), or mod_norm().
method	Estimation method. Current choices are "standard" (the default) and "inner-outer". See below for details.
vars_inner	Names of variables to use for inner model when method is ⁠"inner-outer". If ⁠NULL⁠(the default)⁠vars_inner' is the age, sex/gender, and time variables.
optimizer	Which optimizer to use. Current choices are "multi", "nlminb", "BFGS", and "GC". Default is "multi". See below for details.
quiet	Whether to suppress warnings and progress messages from the optimizer. Default is TRUE.
start_oldpar	Whether the optimizer should start at previous estimates. Used only when fit() is being called on a fitted model. Default is FALSE.
...	Not currently used.

Value

A bage_mod object

Estimation methods

• "standard" All parameters, other than the lowest-level rates, probabilities, or means are jointly estimated within TMB. The default.

• "inner-outer". Multiple-stage estimation, which can be faster than "standard" for models with many parameters. In Step 1, the data is aggregated across all dimensions other than those specified in var_inner, and a model for the inner variables is fitted to the data. In Step 2, the data is aggregated across the remaining variables, and a model for the outer variables is fitted to the data. In Step 3, values for dispersion are calculated. Parameter estimtes from steps 1, 2, and 3 are then combined. "inner-outer" methods are still experimental, and may change in future, eg dividing calculations into chunks in Step 2.

Optimizer

The choices for the optimizer argument are:

• "multi" Try "nlminb", and if that fails, retart from the value where "nlminb" stopped, using "BFGS". The default.

• "nlminb" stats::nlminb()

• "BFGS" stats::optim() using method "BFGS".

• "GC" stats::optim() using method "CG" (conjugate gradient).

See Also

• mod_pois(), mod_binom(), mod_norm() Specify a model

• augment(), components(), tidy() Examine output from a model

• forecast() Forecast, based on a model

• report_sim() Simulation study of a model

• unfit() Reset a model

• is_fitted() Check if a model has been fitted

Examples

## specify model
mod <- mod_pois(injuries ~ age + sex + year,
                data = nzl_injuries,
                exposure = popn)

## examine unfitted model
mod

## fit model
mod <- fit(mod)

## examine fitted model
mod

## extract rates
aug <- augment(mod)
aug

## extract hyper-parameters
comp <- components(mod)
comp

bage documentation built on April 3, 2025, 8:53 p.m.