Returns one tidy row for every registered estimator and workflow. Unlike
equivalence(), which refines the declaration for one fitted object,
equivalence_table() exposes the package-wide evidence boundary before a
model is fitted. A closed evidence status means the declared scope has an
executable oracle, engine, recovery, or internal-consistency contract; it
does not turn native extensions into claims about an unrelated package.
Value
A data frame with method, kind, declared status, evidence status, reference, numerical tolerance bounds, scope, and notes.
Examples
equivalence_table()
#> method kind status evidence_status
#> 10 gimme estimator validated closed
#> 4 graphical_var estimator validated closed
#> 5 graphical_var_each estimator validated closed
#> 13 ml estimator validated_native closed
#> 6 mlvar estimator validated closed
#> 7 mlvar_bayes estimator partial bounded
#> 8 mlvar_mplus estimator delegated conditional
#> 12 rolling_graphical_var estimator validated_internal closed
#> 11 rolling_var estimator validated_internal closed
#> 9 usem estimator validated closed
#> 1 var estimator validated closed
#> 3 var_bayes estimator partial bounded
#> 2 var_each estimator validated closed
#> 16 compare workflow validated_internal closed
#> 17 forecast workflow validated_internal closed
#> 14 preprocess workflow validated_internal closed
#> 15 stability workflow validated_internal closed
#> reference tolerance_min tolerance_max
#> 10 gimme::gimme 10.0 0e+00 5e-05
#> 4 graphicalVAR::graphicalVAR 1e-06 1e-06
#> 5 graphicalVAR::graphicalVAR 1e-06 1e-06
#> 13 base-R engines and closed forms NA NA
#> 6 mlVAR::mlVAR 1e-08 1e-08
#> 7 Mplus DSEM NA NA
#> 8 mlVAR::mlVAR(estimator='Mplus') NA NA
#> 12 idiographic::fit_graphical_var 0e+00 0e+00
#> 11 idiographic::fit_var 0e+00 0e+00
#> 9 lavaan::lavaan 1e-08 1e-08
#> 1 stats::lm.fit 1e-10 1e-10
#> 3 Mplus ESTIMATOR=BAYES 2e-02 3e-02
#> 2 idiographic::fit_var 0e+00 0e+00
#> 16 registered estimator summaries 0e+00 0e+00
#> 17 direct fitted-model prediction 0e+00 0e+00
#> 14 shared lag-design engines 0e+00 0e+00
#> 15 registered base estimators NA NA
#> scope
#> 10 Direct bivariate and three-variable standard/hybrid/VAR oracle matrix covering search outputs, fit statistics, corrections, alpha, stopping rules, standardization, fit/group cutoffs, forced paths, exogenous variables, and uneven panels, plus recovery tests.
#> 4 Supported lag-1 settings, including tested beta/kappa options.
#> 5 Every returned subject fit is compared directly with an upstream lag-1 graphicalVAR fit on the same subject panel.
#> 13 All regression/classification model families, selectors, prediction, and tuning controls are exercised; linear and logistic engines are cell-equal to lm.fit/glm.fit.
#> 6 Direct oracle matrix for every supported lag-1 lmer temporal and contemporaneous structure, plus 20 real ESM fixed/fixed panels.
#> 7 Five fixed bivariate fixtures, one univariate random-AR fixture, multivariate recovery, missing-data recovery, and explicit MCMC control contracts.
#> 8 Complete backend argument-forwarding and output-conversion contract; the statistical estimator is the delegated licensed backend.
#> 12 Every retained window is a registered graphical VAR fit; direct-window equality, boundaries, and planted-change recovery are tested.
#> 11 Every retained window is a registered VAR fit; direct-window equality, boundaries, and planted-change recovery are tested.
#> 9 Fixed-syntax estimates for raw/standardized panels and ML/MLR engines; trimming remains a native search procedure.
#> 1 OLS coefficient engine and package-defined VAR(1) preprocessing.
#> 3 Three frozen bivariate Mplus fixtures, an OLS cross-check, and executable burn-in/thinning/retained-draw contracts.
#> 2 Exact per-subject wrapper behavior.
#> 16 Exact stacking, dispatch, argument routing, and failure isolation.
#> 17 Rolling-origin split geometry, boundary lags, deterministic metrics, and predictions equal direct fitted-model matrix prediction.
#> 14 Exact shared GVAR lag-design equality plus deterministic diagnostic, filtering, detrending, missingness, and threshold contracts.
#> 15 Deterministic block/split-half resampling, ordering invariants, and five-estimator dispatch contracts; no unrelated external target.
#> notes
#> 10 Unsupported S-GIMME, latent-variable, convolution, ordinal, LASSO, and multiple-solution modes error explicitly instead of inheriting this supported-surface claim. gimme 10.0 itself fails on the audited ar=FALSE fixture, so that local mode remains a supported extension.
#> 4 The declared tolerance follows the expanded committed oracle matrix.
#> 5
#> 13
#> 6 Real-panel evidence covers lag 1 with scale=FALSE; the synthetic oracle matrix additionally covers validated multi-lag, preprocessing, and unique-model slices.
#> 7 Full random-slope and missing-data feature equivalence is not established.
#> 8 The committed suite tests the complete wrapper boundary with a contract double. Running Mplus itself remains conditional on a licensed executable.
#> 12
#> 11
#> 9
#> 1 This is engine equivalence, not blanket equivalence to another VAR package.
#> 3 Tolerance is statistical and parameter-dependent.
#> 2
#> 16
#> 17
#> 14
#> 15
equivalence_table("gimme")
#> method kind status evidence_status reference tolerance_min
#> 1 gimme estimator validated closed gimme::gimme 10.0 0
#> tolerance_max
#> 1 5e-05
#> scope
#> 1 Direct bivariate and three-variable standard/hybrid/VAR oracle matrix covering search outputs, fit statistics, corrections, alpha, stopping rules, standardization, fit/group cutoffs, forced paths, exogenous variables, and uneven panels, plus recovery tests.
#> notes
#> 1 Unsupported S-GIMME, latent-variable, convolution, ordinal, LASSO, and multiple-solution modes error explicitly instead of inheriting this supported-surface claim. gimme 10.0 itself fails on the audited ar=FALSE fixture, so that local mode remains a supported extension.