Adaptive round log accessor.

Usage

adaptive_round_log(state, reconstruct_deferred = FALSE)

Arguments

state: Adaptive state.
reconstruct_deferred: Logical; when TRUE, reconstruct deferred audit-only posterior summaries from stored refit payloads when available. By default, returns the canonical stored round_log without reconstruction.

Value

A tibble with one row per completed posterior refit round.

Details

round_log is the canonical per-refit audit log for the adaptive pairing workflow. Each row summarizes one Bayesian BTL refit and includes diagnostics, reliability, and stopping-gate fields used to justify stop decisions.

Core columns:

Refit identity/state: refit_id, round_id_at_refit, step_id_at_refit, timestamp, model_variant, n_items, total_pairs_done, new_pairs_since_last_refit, n_unique_pairs_seen.
Candidate health: proposed_pairs_mode, starve_rate_since_last_refit, fallback_rate_since_last_refit, fallback_used_mode, starvation_reason_mode.
Identifiability/quota adaptation: global_identified, global_identified_reliability_min, global_identified_rank_corr_min, long_quota_raw, long_quota_effective, long_quota_removed, realloc_to_mid, realloc_to_local, phase_scope, phase_scope_set_id, phase_scope_n_items.
Coverage/imbalance: mean_degree, min_degree, mean_degree_scope, min_degree_scope, pos_balance_sd, star_cap_rejects_since_last_refit, star_cap_reject_rate_since_last_refit, recent_deg_median_since_last_refit, recent_deg_max_since_last_refit.
Posterior parameter summaries: epsilon_mean/percentiles and b_mean/percentiles.
Audit diagnostics: ts_sigma_mean, ts_sigma_max, ts_degree_sigma_corr, ts_btl_theta_corr, ts_btl_rank_spearman, ci95_theta_width_*, near_tie_adj_frac, near_tie_adj_count, p_adj_median, cov_trace_theta, cov_logdet_diag_theta, post_sd_theta_p10, post_sd_theta_p50, post_sd_theta_p90, top20_boundary_entropy_*, nn_diff_sd_*.
Stopping diagnostics: diagnostics_pass, diagnostics_divergences_pass, diagnostics_rhat_pass, diagnostics_ess_pass, divergences, divergences_max_allowed, max_rhat, max_rhat_allowed, min_ess_bulk, ess_bulk_required, near_stop_active, reliability_EAP, reliability_EAP_scope, eap_reliability_min, eap_pass, eap_pass_scope, theta_sd_eap, theta_sd_eap_scope, rho_theta, rho_theta_scope, lag_eligible, lag_eligible_scope, theta_corr_min, theta_corr_pass, theta_corr_pass_scope, delta_sd_theta, delta_sd_theta_scope, theta_sd_rel_change_max, delta_sd_theta_pass, delta_sd_theta_pass_scope, rho_rank, rho_rank_scope, rank_spearman_min, rho_rank_pass, rho_rank_pass_scope.
Refit execution metadata: mcmc_chains, mcmc_parallel_chains, mcmc_core_fraction, mcmc_cores_detected_physical, mcmc_cores_detected_logical, mcmc_threads_per_chain, mcmc_cores_available, mcmc_parallel_chains_requested, mcmc_concurrency_budget, mcmc_concurrency_used, mcmc_cmdstanr_version. Requested parallel chains are NA for automatic scheduling; the budget and usage count CPU slots across chains and threads. Historical fits without allocation metadata report NA for those fields.
Stop output: stop_decision, stop_reason, max_pairs_after_stop, pairs_committed_after_stop.

Examples

state <- adaptive_rank_start(c("a", "b", "c"), seed = 1)
adaptive_round_log(state)
#> # A tibble: 0 × 121
#> # ℹ 121 variables: predictive_prior_digest <chr>, refit_id <int>,
#> #   round_id_at_refit <int>, step_id_at_refit <int>, timestamp <dttm>,
#> #   model_variant <chr>, n_items <int>, total_pairs_done <int>,
#> #   new_pairs_since_last_refit <int>, new_active_pairs_since_last_refit <int>,
#> #   new_probe_pairs_since_last_refit <int>,
#> #   new_total_cross_pairs_since_last_refit <int>, n_unique_pairs_seen <int>,
#> #   proposed_pairs_mode <dbl>, starve_rate_since_last_refit <dbl>, …