MAP fit object

MAP fit object

MAP fit object

Details

An R6 class storing optimization results from maximum a posteriori (MAP) estimation.

Super class

BayesRTMB::RTMB_Fit_Base -> map_fit

Public fields

model

The `RTMB_Model` object used for estimation.

par_vec

Parameter vector on the unconstrained scale.

par

Parameter list on the constrained scale.

objective

RTMB objective function object.

log_ml

Log marginal likelihood or related model criterion.

convergence

Optimizer convergence code.

sd_rep

Standard deviation report object.

df_fixed

Summary table for fixed-effect parameters.

random_effects

Random effect estimates.

df_transform

Summary table for transformed parameter estimates.

df_generate

Summary table for generated quantity estimates.

opt_history

A vector of optimize objective history.

transform

List of transformed parameters maintaining their original dimensions.

generate

List of generated quantities maintaining their original dimensions.

se_samples

List of simulated samples for standard error estimation.

Methods

Public methods

• MAP_Fit$get_point_estimate()

• MAP_Fit$EAP()

• MAP_Fit$MAP()

• MAP_Fit$new()

• MAP_Fit$summary()

• MAP_Fit$print()

• MAP_Fit$generated_quantities()

• MAP_Fit$clone()

Inherited methods

• BayesRTMB::RTMB_Fit_Base$fa_rotate()
• BayesRTMB::RTMB_Fit_Base$rotate()

---

Method get_point_estimate()

Get point estimate for a target parameter (internal use).

Usage

MAP_Fit$get_point_estimate(target)

Arguments

target

Target parameter name.

Returns

Matrix or array of point estimate.

---

Method EAP()

Return point estimates (EAP is not applicable).

Usage

MAP_Fit$EAP(...)

Arguments

...

Ignored.

Returns

A named list of point estimates.

---

Method MAP()

Return point estimates (MAP sampling method is not applicable).

Usage

MAP_Fit$MAP(...)

Arguments

...

Ignored.

Returns

A named list of point estimates.

---

Method new()

Create a new `MAP_Fit` object.

Usage

MAP_Fit$new(
  model,
  par_vec,
  par,
  objective,
  log_ml,
  convergence,
  sd_rep,
  df_fixed,
  random_effects,
  df_transform = NULL,
  df_generate = NULL,
  opt_history = NULL,
  transform = NULL,
  generate = NULL,
  se_samples = NULL
)

Arguments

model

The `RTMB_Model` object used for estimation.

par_vec

Parameter vector on the unconstrained scale.

par

Parameter list on the constrained scale.

objective

RTMB objective function object.

log_ml

Log marginal likelihood or related model criterion.

convergence

Optimizer convergence code.

sd_rep

Standard deviation report object.

df_fixed

Summary table for fixed-effect parameters.

random_effects

Random effect estimates.

df_transform

Summary table for transformed parameter estimates.

df_generate

Summary table for generated quantity estimates.

opt_history

A vector of optimize objective history.

transform

List of transformed parameters maintaining their original dimensions.

generate

List of generated quantities maintaining their original dimensions.

se_samples

List of simulated samples for standard error estimation.

---

Method summary()

Summarize MAP estimates.

Usage

MAP_Fit$summary(pars = NULL, max_rows = 10, digits = 5)

Arguments

pars

Character vector specifying the names of parameters to summarize. If NULL, all available parameters are summarized.

max_rows

Maximum number of rows to print in summaries. Default is 10.

digits

Number of digits to print.

Returns

A summary object, typically a data frame.

---

Method print()

Print a brief summary of the fitted object.

Usage

MAP_Fit$print(pars = NULL, max_rows = 10, digits = 5, ...)

Arguments

pars

Character vector specifying the names of parameters to summarize.

max_rows

Maximum number of rows to print in summaries.

digits

Number of digits to print.

...

Additional arguments passed to the `summary` method.

Returns

The object itself, invisibly.

---

Method generated_quantities()

Compute generated quantities from the MAP estimate.

Usage

MAP_Fit$generated_quantities(code)

Arguments

code

An `rtmb_code({ ... })` or `{ ... }` block containing the logic to be calculated using the MAP estimate.

Returns

The `MAP_Fit` object itself (invisibly). Results are added or updated in the `generate` list and `df_generate`.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

MAP_Fit$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.