summary.badp_model_space: Summarize a Model Space Object

In badp: Bayesian Averaging for Dynamic Panels

Summarize a Model Space Object

Description

Summary method for objects of class badp_model_space. Replaces the default summary() output (which just lists the structure of the underlying list) with a structured object describing the dimensions of the model space, its variables, and a brief look at the per-model log-likelihoods stored in object$stats.

Usage

## S3 method for class 'badp_model_space'
summary(object, ...)

Arguments

object	An object of class badp_model_space, typically the result of optim_model_space.
...	Additional arguments (currently unused).

Value

An object of class summary.badp_model_space containing:

• num_models - Number of models in the model space (2^R).

• num_regressors - Number of regressors excluding the lagged dependent variable (R).

• num_params - Number of parameters in the full parameter vector (rows of object$params).

• observations_num - Number of observations used.

• is_nested - Logical, whether the model space is nested.

• reg_names - All variable names (lagged dependent first).

• dep_var_name - The (lagged) dependent variable name.

• regressor_names - The regressor names.

• data_dim - Dimensions of the source data frame, or NULL if not stored.

• likelihoods - Per-model log-likelihood values (row 1 of object$stats), or NULL if not available.

• num_nonconverged - Number of models whose optimization did not converge, or NULL if the model space carries no convergence diagnostics (e.g. objects created before badp 0.6.0).

See Also

print.badp_model_space, print.summary.badp_model_space, optim_model_space, bma

Examples

data(full_model_space)
summary(full_model_space)

badp documentation built on Aug. 20, 2026, 9:08 a.m.