Abstract Fitter Class

Abstract base class for Bayesian model fitters in bayesim.

The Fitter class defines the interface that all model fitters must implement. It provides a consistent API for fitting Bayesian models, extracting posterior draws, generating predictions, computing log-likelihoods, and performing model diagnostics.

Usage

Fitter(
  name = character(0),
  supports_predictions = TRUE,
  supports_log_lik = TRUE,
  supports_loo = TRUE
)

Arguments

name

Character string identifying the fitter (e.g., "stan", "brms")

supports_predictions

Logical indicating if the fitter supports predictions

supports_log_lik

Logical indicating if the fitter supports log-likelihood computation

supports_loo

Logical indicating if the fitter supports LOO-CV

Value

An S7 class object representing the abstract Fitter

Methods

The following S7 generics must be implemented by subclasses:

fit(fitter, data_bundle, fit_spec, seed, task_ctx)

Main fitting method

extract_draws(fitter, fit_result, variables = NULL)

Extract posterior draws

predict_fit(fitter, fit_result, newdata = NULL, seed = NULL)

Generate predictions

log_lik(fitter, fit_result, newdata = NULL)

Pointwise log-likelihood

loo(fitter, fit_result)

LOO-CV computation

diagnostics(fitter, fit_result)

Extract fit diagnostics

Creating Custom Fitters

To create a custom fitter, extend this class and implement methods for the S7 generics: fit(), extract_draws(), predict(), log_lik(), loo(), diagnostics().

See also

MockFitter for a simple example implementation