| 030-measurement-intelligence-utils | Measurement-intelligence plotting and result infrastructure |
| 031-probabilistic-aoi | Probabilistic AOI assignment and uncertainty propagation |
| 032-compositional-aoi | Compositional analysis of AOI attention |
| 033-process-uncertainty | Process measurement-uncertainty budgets |
| 034-calibration-recalibration | Calibration drift and offline recalibration |
| 035-process-reliability | Process reliability and Generalizability Theory |
| 036-device-linking | Cross-device and cross-vendor metric linking |
| 037-pupil-registration | Pupil phase-amplitude registration |
| 038-informative-missingness | Informative missingness and MNAR sensitivity |
| 039-recurrence-analysis | Recurrence and cross-recurrence analysis |
| 040-fixation-point-process | Spatio-temporal fixation point-process models |
| 041-representative-scanpaths | Representative scanpaths and scanpath distributions |
| 042-process-episodes | Cognitive-episode change-point detection |
| 043-item-bank-optimization | Multi-objective item-bank optimization |
| 044-process-dif-fairness | Dynamic process-DIF and fairness drift |
| 045-process-norms | Conditional process reference centiles |
| 046-evidence-provenance-graph | Evidence and decision provenance graphs |
| 047-measurement-intelligence-adapters | Measurement-intelligence compatibility adapters |
| ablate_multimodal_channels | Create formal channel-ablation datasets |
| addm_glam_proxy_features | Compute aDDM/GLAM-inspired gaze-evidence proxy features |
| adjust_pupil_confounds | Extract confound-adjusted pupil values |
| advanced_model_evidence_spec | Specify evidence required to promote advanced model... |
| advanced_validation_grid | Construct the advanced-model validation grid |
| algorithm_facet_effects | Extract algorithm facet effects |
| analysis_decision_entropy | Entropy of an explicitly enumerated analysis-decision space |
| analysis_environment_snapshot | Snapshot an eyeprocess analysis environment |
| analysis_resolution_guard | Audit compatibility between measurement resolution and an... |
| aoi_membership_probability | AOI membership probabilities from uncertainty draws |
| aoi_trajectory_features | Extract AOI growth-curve/trajectory features |
| api_family_map | Map exported APIs to conceptual families |
| api_lifecycle_diff | Compare two API lifecycle registries |
| api_surface_summary | Summarise API surface by family and lifecycle status |
| apply_preflight_decision | Apply a pre-flight decision to data explicitly |
| apply_synthetic_corruption | Apply a synthetic corruption plan |
| as_irt_recovery_results | Canonicalise parameter-recovery results |
| assign_process_feature_family | Assign features to conservative process-feature families |
| audit_3pl_process_signatures | Identify items for descriptive 3PL/process review |
| audit_advanced_model_evidence | Audit advanced-model scientific evidence |
| audit_benchmark_release | Audit whether benchmark assets are ready for public release |
| audit_bias | Audit bias |
| audit_biometric_imputation | Alias emphasizing sensitivity rather than automatic... |
| audit_biometric_preflight | Audit incoming biometric/process data before modelling |
| audit_candidate_item_bank | Audit a candidate item bank against a seed model |
| audit_channel_incremental_information | Audit out-of-sample incremental information from a process... |
| audit_convergence | Audit convergence and classified failures |
| audit_coverage | Audit coverage |
| audit_decision_provenance | Audit decision provenance and completeness |
| audit_distractor_attention | Audit distractor attention patterns |
| audit_eye_api | Audit API lifecycle completeness and replacement contracts |
| audit_eye_pipeline | Audit a pipeline definition or completed run |
| audit_frontier_model_contract | Audit whether a gated frontier model has a minimum evidence... |
| audit_identifiability | Audit empirical identifiability from replicate estimates |
| audit_interval_width | Audit interval width |
| audit_irf_shape | Audit item response-function shape departures |
| audit_item_reduction_sensitivity | Run stepwise Rasch item-reduction as a sensitivity analysis |
| audit_latent_distribution | Audit the empirical latent-trait distribution |
| audit_measurement_transportability | Summarise measurement transportability across held-out groups |
| audit_model_promotion | Audit promotion readiness for advanced model families |
| audit_multimodal_identifiability | Audit basic multimodal design identifiability |
| audit_multimodal_m2_identifiability | Audit structural and data identifiability for M0-M2 |
| audit_multimodal_m3_identifiability | Audit structural and measurement support for M3 |
| audit_multimodal_m4_identifiability | Audit M4 structural and posterior identifiability |
| audit_multimodal_measurement | Audit a multimodal measurement object |
| audit_multivariate_process_quality | Alias emphasizing data-quality interpretation of process... |
| audit_nonparametric_rasch | Run nonparametric Rasch diagnostics with eRm |
| audit_presentation_accessibility | Audit presentation/accessibility sensitivity without clinical... |
| audit_process_adjusted_dif | Audit DIF before and after process-data adjustment |
| audit_process_anomalies | Audit multivariate process/data-quality anomalies |
| audit_process_drift | Audit post-deployment psychometric and biometric drift |
| audit_process_external_validity | Audit external/structural validity of process traits |
| audit_process_local_dependence | Audit inter-option/process local dependence |
| audit_process_measurement_invariance | Audit process measurement invariance across facets |
| audit_process_window_sensitivity | Audit sensitivity of process summaries to temporal window... |
| audit_pupil_fatigue_drift | Audit within-person pupil fatigue/trial-order drift |
| audit_pupil_frequency_stability | Audit stability of pupil frequency features across window... |
| audit_pupil_preprocessing_order | Audit declared order of pupil preprocessing steps |
| audit_rmse | Audit rmse |
| audit_roundtrip_loss | Audit semantic and numerical loss after a round trip |
| audit_sampling_irregularity | Audit sampling irregularity |
| audit_sbc | Audit SBC rank uniformity |
| audit_signal_filter | Summarize a signal-filter audit |
| audit_temporal_leakage | Audit temporal leakage in a feature provenance table |
| audit_validation_completion | Audit whether a validation programme is complete |
| audit_vendor_field_coverage | Audit vendor field coverage against canonical semantics |
| audit_vendor_validation | Audit a multi-vendor validation corpus |
| audit_visual_context_dependence | Audit visual-context dependence |
| bayesian_process_diagnostic_flags | Extract compact Bayesian process-model diagnostic flags |
| bayesian_process_diagnostics_dashboard | Summarize Bayesian process-model diagnostics |
| benchmark_expected_outputs | Return expected benchmark outputs |
| benchmark_eyeprocess | Benchmark an eyeprocess operation |
| benchmark_eye_storage | Benchmark storage formats and query operations |
| benchmark_memory_estimate | Memory estimate for an R object or generated problem size |
| benchmark_scaling_curve | Estimate scaling exponent from benchmark results |
| bind_process_windows | Bind compatible process-window objects |
| biometric_imputation_sensitivity | Run biometric-feature imputation as a sensitivity analysis |
| bootstrap_process_reliability | Bootstrap ICC reliability by resampling participants |
| build_compatibility_matrix | Build the declared/fixture/empirical compatibility matrix |
| build_gazepoint_media_trials | Reconstruct media presentations as analysis trials |
| calibration_drift_profile | Calibration drift profile across sessions/batches |
| calibration_error_model | Build an empirical bivariate calibration-error model |
| calibration_sensitivity_grid | Sensitivity grid for deterministic calibration offsets |
| calibration_transfer_audit | Audit transfer of calibration across devices/sessions/sites |
| canonical_eye_api | Canonical API mapping |
| classify_item_missingness | Classify item missingness using exposure and response... |
| collect_eye_storage | Collect a disk-backed eye dataset |
| collect_validation_evidence | Collect validation evidence into a common bundle |
| collect_validation_jobs | Collect validation checkpoints from one or more directories |
| compare_aoi_methods | Compare explicit AOI assignment methods |
| compare_aoi_trajectories | Compare AOI trajectory feature objects |
| compare_bayesian_process_models | Compare Bayesian process models by LOO or Bayes factor |
| compare_decision_manifests | Compare two research decision manifests |
| compare_deployment_batches | Compare two deployment batches descriptively |
| compare_diffusion_accuracy_rt | Compare diffusion and conventional accuracy-RT models |
| compare_dynamic_transition_models | Compare dynamic transition models |
| compare_engine_adapters | Compare multiple external-engine adapter results |
| compare_fixation_methods | Compare explicit fixation-detection methods |
| compare_functional_scalar_models | Compare functional and scalar pupil summaries |
| compare_hard_probabilistic_aoi | Compare hard and probabilistic AOI assignments |
| compare_irt_models | Compare multimodal IRT model objects |
| compare_latent_distribution_models | Compare simple latent-distribution reference models |
| compare_model_engines | Compare equivalent model engines |
| compare_parametric_nonparametric_irf | Compare conventional logistic and flexible IRF shapes |
| compare_presentation_fairness | Compare outcomes across presentation variants |
| compare_process_criterion_models | Compare process external-validity models |
| compare_process_models | Compare explicit process-model specifications |
| compare_process_profile_solutions | Compare candidate process-profile solutions |
| compare_pupil_kernels | Compare pupil deconvolution kernels |
| compare_pupil_preprocessing | Compare explicit pupil-preprocessing methods |
| compare_raw_adjusted_pupil | Compare raw and confound-adjusted pupil values |
| compare_reproducibility_fingerprints | Compare two reproducibility fingerprints |
| compare_signal_filters | Compare multiple signal filters |
| compare_strategy_heterogeneity | Compare mixture and continuous heterogeneity descriptions |
| compare_validation_engines | Compare validation engines on common recovery output |
| compare_vendor_semantics | Compare semantic mappings between vendors |
| compare_visual_context_irt | Compare base and visual-context IRT models |
| compatibility_evidence_matrix | Build a detailed compatibility evidence matrix |
| context_factor_effects | Extract visual-context factor effects/loadings |
| coordinate_fidelity_audit | Coordinate semantic-fidelity audit |
| coverage_calibration_curve | Interval coverage calibration curve |
| create_public_benchmark | Create a public, de-identified benchmark bundle |
| cross_device_process_equating_audit | Cross-device process-scale equating audit |
| crossed_grouped_cv | Cross-classified grouped cross-validation |
| crossed_grouped_folds | Create cross-classified grouped folds |
| cross_version_adapter_regression | Compare adapter output across software/format versions |
| data_quality_reporting_table | Compact reporting table for eye-tracking data quality |
| decision_manifest_diff | Alias for manifest comparison emphasizing changed decision... |
| decision_manifest_hash | Stable hash of decision content |
| decision_manifest_table | Flatten a decision manifest to a table |
| decision_space_coverage | Coverage of a declared decision space by evaluated... |
| decision_stability | Overall decision-stability summary |
| decode_dynamic_states | Decode latent or fitted transition states |
| derive_gazepoint_workflow_features | Derive the complete Gazepoint workflow feature set |
| detect_corrupt_partitions | Detect missing, truncated, or modified partitions |
| detect_irt_changepoints | Detect IRT/process change points using an SIC-inspired... |
| detect_process_changepoint | Detect a response-process change point |
| device_facet_effects | Extract device facet effects |
| diffusion_identification_study | Construct a simulation-based identification study |
| diffusion_parameter_diagnostics | Diagnose diffusion-parameter trade-offs and sampling |
| diffusion_posterior_predictive | Posterior predictive summaries for accuracy and RT |
| distractor_process_map | Build a distractor process map |
| drift_by_device | Drift audit stratified by device |
| drift_by_site | Drift audit stratified by study site |
| drift_by_stimulus_version | Drift audit stratified by stimulus version |
| drift_by_vendor | Drift audit stratified by vendor |
| dynamic_irtree_recovery | Evaluate dynamic-state recovery under misclassification |
| dynamic_irtree_spec | Specify a hardened dynamic gaze-state IRTree |
| dynamic_posterior_predictive_check | Posterior predictive checks for dynamic state models |
| dynamic_transition_design | Build an explicit dynamic-transition design matrix |
| effective_sampling_frequency | Estimate effective sampling frequency from timestamps |
| encode_response_combinations | Encode multiple-response item response combinations |
| engine_adapter_status | Report an adapter's availability and contract |
| equate_irt_scales | Equate IRT scales using anchor item parameters |
| estimate_calibration_error | Estimate empirical calibration/validation error |
| estimate_visual_exposure_probability | Estimate visual exposure probability |
| evaluate_validation_acceptance | Evaluate a validation acceptance rule |
| event_marker_qc | Event-marker plausibility audit |
| event_roundtrip_audit | Audit event survival across an interchange round trip |
| event_semantics_audit | Audit event semantic preservation |
| expand_eyeprocess_stress_evidence_plan | Expand a stress evidence plan into one-factor-at-a-time... |
| expand_eyeprocess_validation_plan | Expand a validation-evidence plan to a scenario table |
| expand_process_validation_design | Expand a process-validation design into explicit conditions |
| expected_process_information | Expected process-aware item utility under a theta... |
| explain_latent_interaction | Explain local person-item latent-space interactions |
| export_eye_bids | Export Eye-Tracking-BIDS physiological recordings |
| export_eye_pipeline | Export a pipeline manifest and optional run status |
| export_prov_json | Export lightweight PROV-oriented JSON |
| export_ro_crate_metadata | Export minimal RO-Crate 1.3 metadata |
| export_validation_bundle | Export a validation evidence bundle |
| external_eye_adapters | Convert common external eye-tracking objects |
| external_model_engines | List external engine adapters |
| external_validate_irt | External validation on a completely held-out dataset |
| extract_diffusion_parameters | Extract diffusion parameter summaries |
| extract_functional_pupil_parameters | Extract functional pupil parameters for validation |
| extract_parameter_truth | Extract canonical parameter truth from simulated data |
| extract_process_windows | Extract standardized sliding-window process features |
| eye_analysis_pipeline | Construct a governed analysis pipeline |
| eye_analysis_spec | Define explicit analysis decisions for an eyeprocess workflow |
| eye_api_inventory | Inventory the public eyeprocess API |
| eye_api_lifecycle | Normalize or create an API lifecycle registry |
| eye_api_recommendation | Lifecycle recommendation for API review |
| eye_api_status | Lookup lifecycle status for one or more APIs |
| eye_api_superseded | Return superseded/deprecated compatibility interfaces |
| eye_benchmark_design | Define a computational benchmark design |
| eye_decision_manifest | Create a machine-readable research decision manifest |
| eye_pipeline_dot | Render pipeline dependencies as Graphviz DOT |
| eye_pipeline_graph | Return pipeline vertices and dependency edges |
| eye_pipeline_manifest | Machine-readable pipeline manifest |
| eye_pipeline_mermaid | Render pipeline dependencies as Mermaid flowchart text |
| eye_pipeline_step | Define a governed pipeline step |
| eyeprocess-adapters | Mappings and adapter registry |
| eyeprocess_api_version | Return the public eyeprocess API version |
| eyeprocess_benchmark_study | Locate the bundled public benchmark study |
| eyeprocess_cdm_attribute_profiles | Enumerate latent attribute profiles |
| eyeprocess_cdm_classification_uncertainty | Summarise CDM classification uncertainty from profile... |
| eyeprocess_cdm_dina_ideal_response | Compute deterministic DINA ideal responses from a Q-matrix |
| eyeprocess_cdm_dina_probability | DINA response probabilities from slip and guess parameters |
| eyeprocess_cdm_qmatrix_audit | Audit a cognitive-diagnosis Q-matrix |
| eyeprocess-class | Create and manage eyeprocess datasets |
| eyeprocess-coordinates-time | Coordinate and timebase management |
| eyeprocess_deprecation | Declare a deprecation in a structured form |
| eyeprocess-experimental | Experimental psychometric process models |
| eyeprocess-export-report | Export, reporting, and package bridges |
| eyeprocess-features | Derive gaze, pupil, response-time, and biometric features |
| eyeprocess-format-validation | Validate real eye-tracking exports and compatibility corpora |
| eyeprocess-import-gazepoint | Import Gazepoint and Gazepoint Biometrics exports |
| eyeprocess-import-generic | Import generic delimited eye-tracking data |
| eyeprocess-import-vendors | Import Tobii, Pupil Labs, EyeLink, and SMI exports |
| eyeprocess_irt_2pl_probability | 2PL item-response probability |
| eyeprocess_irt_3pl_probability | 3PL item-response probability |
| eyeprocess_irt_4pl_probability | 4PL item-response probability |
| eyeprocess_irt_adaptive_trace | Create an auditable adaptive-testing trace |
| eyeprocess_irt_anchor_audit | Audit candidate anchor items using supplied DIF evidence |
| eyeprocess_irt_anchor_purification | Iteratively remove anchors exceeding a supplied effect... |
| eyeprocess_irt_apply_link | Apply linear IRT scale-linking coefficients |
| eyeprocess_irt_bank_coverage | Audit item-bank information coverage across a theta region |
| eyeprocess_irt_category_function_audit | Audit category probability functions |
| eyeprocess_irt_classification_precision | Summarise decision precision at one or more theta cut scores |
| eyeprocess_irt_conditional_sem | Conditional standard error from information |
| eyeprocess_irt_content_balance_audit | Audit content balance in an administered adaptive form |
| eyeprocess_irt_device_drift | Summarise parameter drift across acquisition devices |
| eyeprocess_irt_dif_effect_curve | Differential item functioning effect curve from two parameter... |
| eyeprocess_irt_dtf_curve | Differential test functioning effect curve |
| eyeprocess_irt_eap_score | EAP score for dichotomous IRT item parameters |
| eyeprocess_irt_engine_evidence_table | Build an external-engine capability and availability table |
| eyeprocess_irt_engine_registry | Registry of specialized external IRT engines |
| eyeprocess_irt_engine_status | Query an external IRT engine |
| eyeprocess_irt_expected_score | Expected item score |
| eyeprocess_irt_exposure_summary | Summarise item exposure rates |
| eyeprocess_irt_extreme_score_audit | Audit extreme response scores without assigning behavioral... |
| eyeprocess_irt_fit_dashboard | Build an integrated IRT diagnostic dashboard object |
| eyeprocess_irt_functioning_effect_summary | Summarise DIF/DTF curve magnitude |
| eyeprocess_irt_gpcm_probability | Generalized partial-credit category probabilities |
| eyeprocess_irt_grm_probability | Graded-response category probabilities |
| eyeprocess_irt_haebara_link | Haebara item-characteristic-curve linking |
| eyeprocess_irt_identification_audit | Audit IRT scale/location identification |
| eyeprocess_irt_infit_outfit | Compute residual-based Infit and Outfit summaries |
| eyeprocess_irt_information_area | Area under an information curve |
| eyeprocess_irt_information_gain | Information gain between two conditional standard errors |
| eyeprocess_irt_information_targeting | Audit how well item information targets a theta distribution |
| eyeprocess_irt_invariance_evidence | Combine invariance evidence without converting it to a binary... |
| eyeprocess_irt_item_bank | Item bank object for adaptive design |
| eyeprocess_irt_item_fit_residuals | Compute item residual fit summaries from observed and... |
| eyeprocess_irt_item_information | Compute item information for transparent IRT families |
| eyeprocess_irt_item_selection | Select the most informative eligible item at a theta estimate |
| eyeprocess_irt_latent_regression_design | Build a latent-regression design matrix with explicit... |
| eyeprocess_irt_link_stability | Compare linking estimates across anchor subsets |
| eyeprocess_irt_local_dependence_pairs | Extract high residual-dependence item pairs |
| eyeprocess_irt_map_score | MAP score for dichotomous IRT item parameters |
| eyeprocess_irt_marginal_reliability | Marginal reliability from latent-score variance and... |
| eyeprocess_irt_mean_mean_link | Mean-mean IRT linking coefficients |
| eyeprocess_irt_mean_sigma_link | Mean-sigma IRT linking coefficients |
| eyeprocess_irt_measurement_precision_profile | Summarise measurement precision across a theta region |
| eyeprocess_irt_missing_by_design_audit | Audit missing-by-design structure in an IRT response matrix |
| eyeprocess_irt_misspecification_metrics | Compare recovery under reference and misspecified scenarios |
| eyeprocess_irt_misspecification_suite | Create a model-misspecification suite |
| eyeprocess_irt_mle_score | Bounded ML score for dichotomous IRT item parameters |
| eyeprocess_irt_model_card | Create a governed IRT model card |
| eyeprocess_irt_model_card_audit | Audit completeness of an IRT model card |
| eyeprocess_irt_model_spec | Declare an eyeprocess IRT model specification |
| eyeprocess_irt_monotonicity_audit | Audit monotonicity of an item response curve |
| eyeprocess_irt_nominal_probability | Nominal-response category probabilities |
| eyeprocess_irt_parameter_plausibility_audit | Audit basic plausibility of dichotomous item parameters |
| eyeprocess_irt_person_fit_lz | Standardized log-likelihood person-fit diagnostic |
| eyeprocess_irt_person_fit_residuals | Compute person residual fit summaries |
| eyeprocess_irt_plausible_values | Draw plausible values from a discrete posterior grid |
| eyeprocess_irt_ppc_discrepancy | Compare observed and replicated IRT discrepancy statistics |
| eyeprocess_irt_precision_evidence_table | Build a paper-ready IRT information/precision table |
| eyeprocess_irt_prior_sensitivity_grid | Construct a prior-sensitivity grid for Bayesian IRT analyses |
| eyeprocess_irt_prior_sensitivity_summary | Summarise sensitivity of an estimand across declared prior... |
| eyeprocess_irt_prior_spec | Declare prior families for Bayesian IRT engine adapters |
| eyeprocess_irt_process_alignment | Align item parameters with process-channel summaries |
| eyeprocess_irt_process_aware_selection_penalty | Process-aware selection penalty without mental-state... |
| eyeprocess_irt_process_dif_concordance | Compare psychometric DIF effect sizes with process-channel... |
| eyeprocess_irt_q3 | Compute Yen-style Q3 residual correlations |
| eyeprocess_irt_recovery_design | Create an IRT recovery design |
| eyeprocess_irt_recovery_failures | Summarise recovery failure rates |
| eyeprocess_irt_recovery_summary | Summarise IRT parameter recovery |
| eyeprocess_irt_sbc_ranks | Construct SBC ranks from scalar truths and posterior draws |
| eyeprocess_irt_sbc_summary | Summarise IRT SBC ranks with the package SBC diagnostics |
| eyeprocess_irt_score_table | Score a response matrix with EAP, MAP, or ML |
| eyeprocess_irt_score_uncertainty | Summarise score uncertainty |
| eyeprocess_irt_session_drift | Summarise item-parameter drift over sessions |
| eyeprocess_irt_sparse_design_audit | Audit sparse person-item response coverage |
| eyeprocess_irt_stocking_lord_link | Stocking-Lord characteristic-curve linking |
| eyeprocess_irt_stopping_rule | Evaluate a simple adaptive stopping rule |
| eyeprocess_irt_targeting_gap | Compare an examinee distribution with item-bank targeting |
| eyeprocess_irt_test_characteristic_curve | Test characteristic curve for dichotomous item parameters |
| eyeprocess_irt_test_information | Compute a test information curve from item parameters |
| eyeprocess_irt_testlet_audit | Audit testlet sizes and singleton structures |
| eyeprocess_irt_testlet_spec | Declare a testlet structure for bifactor/two-tier IRT engines |
| eyeprocess_irt_threshold_order_audit | Audit ordered category thresholds |
| eyeprocess_joint_process_irt_spec | Declare a response/process joint IRT specification |
| eyeprocess_mirt_directional_information | Directional multidimensional 2PL information |
| eyeprocess_mirt_information_matrix | Multidimensional 2PL item information matrix |
| eyeprocess_mirt_loading_audit | Audit multidimensional IRT loading coverage |
| eyeprocess_mirt_loading_spec | Declare a multidimensional IRT loading structure |
| eyeprocess-models | Psychometric and process-data models |
| eyeprocess_multichannel_measurement_map | Construct a multichannel measurement map |
| eyeprocess_negative_control_evidence_plan | Declare negative-control evidence targets |
| eyeprocess_negative_control_evidence_table | Build a paper-ready negative-control table |
| eyeprocess-package | eyeprocess: Harmonize Eye-Tracking and Psychometric Process... |
| eyeprocess-plots | Visualize eye-tracking and multimodal process data |
| eyeprocess-preprocessing | Gaze and pupil preprocessing |
| eyeprocess_process_irt_data_bundle | Prepare a sparse response/process bundle for external joint... |
| eyeprocess_process_item_profile | Aggregate process channels by item |
| eyeprocess_process_missingness_pattern | Summarise missingness patterns across response and process... |
| eyeprocess_process_person_profile | Aggregate process channels by person |
| eyeprocess-quality | Quality control, sensitivity, and governance |
| eyeprocess_recovery_evidence_table | Build a paper-ready parameter-recovery table |
| eyeprocess_reliability_evidence_plan | Declare reliability evidence targets |
| eyeprocess_reliability_evidence_table | Build a paper-ready reliability table |
| eyeprocess_response_time_profile | Summarise response-time structure for joint IRT work |
| eyeprocess_sbc_evidence_table | Build a paper-ready SBC table |
| eyeprocess-schema | Canonical schemas and coordinate spaces |
| eyeprocess-simulation | Simulate and validate eyeprocess workflows |
| eyeprocess_speed_accuracy_profile | Describe speed-accuracy association without causal... |
| eyeprocess_stress_evidence_plan | Declare the Milestone #2 measurement-quality stress evidence... |
| eyeprocess_stress_evidence_table | Build a paper-ready stress-test table |
| eyeprocess-trials-aoi | Trials, responses, stimuli, and areas of interest |
| eyeprocess_validation_atlas_gaps | Summarise gaps in a validation evidence atlas |
| eyeprocess_validation_claim_matrix | Build a machine-readable validation claim/evidence matrix |
| eyeprocess_validation_evidence_atlas | Assemble a validation evidence atlas |
| eyeprocess_validation_evidence_grade | Grade the completeness of validation evidence |
| eyeprocess_validation_evidence_index | Create an index over frozen validation evidence artifacts |
| eyeprocess_validation_evidence_manifest | Create an evidence manifest from files and in-memory objects |
| eyeprocess_validation_plan | Declare an eyeprocess validation-evidence plan |
| eyeprocess_validation_readiness | Evaluate readiness of a Milestone #2 validation evidence... |
| eyeprocess_validation_release_gate | Apply a conservative software-release evidence gate |
| eyeprocess_validation_seed | Derive a deterministic bounded validation seed |
| eye_prov_graph | Construct a lightweight provenance graph |
| eye_reproducibility_fingerprint | Construct a reproducibility fingerprint |
| eye_session_manifest | Create a session-level provenance manifest |
| eye_storage_spec | Specify disk-backed eyeprocess storage |
| eye_stream_fidelity_audit | Audit preservation of monocular/binocular stream semantics |
| eye_targets_manifest | Create a targets-compatible dependency manifest |
| facet_effects | Extract facet effects from a many-facet process model |
| field_fidelity_report | Field-level semantic fidelity report |
| file_hash_manifest | Build a file hash manifest |
| filter_eye_signal | Filter a one-dimensional eye signal robustly |
| filter_pupil_signal | Filter pupil signal robustly |
| find_process_measures | Find process measures by channel, level, status, or text |
| fingerprint_validation_case | Fingerprint every file in a validation case |
| fit_aoi_growth_curve | Fit a single AOI growth curve |
| fit_brms_adapter | fit brms adapter |
| fit_censored_normal_process_irt | Conditional censored-normal calibration for bounded process... |
| fit_changepoint_multimodal_irt | Fit a multimodal change-point IRT workflow |
| fit_changepoint_rt_irt | Fit a change-point RT IRT workflow |
| fit_cognitive_diagnosis_process | Cognitive-diagnosis model with process indicators |
| fit_continuous_time_irt | Continuous-time IRT external-engine gate |
| fit_crossclassified_process_irt | Cross-classified process IRT reference model |
| fit_crossclassified_process_irt_mhrm | Create a gated scalable cross-classified MH-RM process IRT... |
| fit_diffirt_adapter | Fit a diffusion IRT adapter |
| fit_diffirt_engine_adapter | fit diffirt engine adapter |
| fit_dynamic_gpirt | Dynamic GPIRT external-engine gate |
| fit_dynamic_irtree | Fit a dynamic gaze-state response-tree model |
| fit_dynamic_irtree_stan | Fit an optional CmdStan dynamic-transition model |
| fit_event_time_irt | Fit an event-time IRT reference workflow |
| fit_external_engine | Fit an external model engine through a stable adapter |
| fit_eyeprocess_erm | Fit an eRm Rasch-family model without fallback substitution |
| fit_eyeprocess_gdina | Fit a G-DINA cognitive-diagnosis model without fallback... |
| fit_eyeprocess_lnirt | Fit a joint response/response-time LNIRT model without... |
| fit_eyeprocess_mirt | Fit a model with mirt without substituting another estimator |
| fit_eyeprocess_tam | Fit a TAM model without substituting another estimator |
| fit_eyetrackingr_adapter | fit eyetrackingr adapter |
| fit_flow_mirt | Flow-MIRT external-engine gate |
| fit_functional_pupil_stan | Fit the bundled joint functional pupil-IRT Stan model |
| fit_gaze_anchored_3pl_audit | Fit a standard 3PL and audit lower-asymptote alignment with... |
| fit_gaze_diffusion_irt | Fit a gaze-informed diffusion model |
| fit_gaze_diffusion_stan | Fit the CmdStan Wiener diffusion model |
| fit_gaze_informed_missingness_irt | Fit a gaze-informed missingness IRT diagnostic |
| fit_gdina_adapter | fit gdina adapter |
| fit_gpirt | GPIRT model-criticism interface |
| fit_irt_model | Fit a registered multimodal IRT model |
| fit_item_parameter_seed_model | Fit an experimental pre-pilot item-parameter seeding model |
| fit_joint_functional_pupil_irt | Fit a functional pupil-informed IRT workflow |
| fit_joint_gaze_rt_irt | Joint response, response-time, and gaze-process IRT |
| fit_joint_graded_rt_process_irt | Joint graded-response, RT, and process reference model |
| fit_kde_latent_distribution_irt | Create a gated KDE latent-distribution IRT interface |
| fit_latent_class_process_irt | Latent process-class IRT reference model |
| fit_latent_space_irt | Fit a latent-space IRT model using LSMjml |
| fit_lnirt_adapter | fit lnirt adapter |
| fit_manyfacet_process_irt | Many-facet process IRT reference model |
| fit_mirt_adapter | fit mirt adapter |
| fit_mixture_irt_process_classes | Fit a true mirt mixture-IRT response model |
| fit_multiblock_process_map | Fit a multiblock psychometric/gaze/pupil/quality structure... |
| fit_multimodal_m2 | Fit the M2 response + RT + gaze reference model |
| fit_multimodal_m3 | Fit the M3 response + RT + gaze + pupil reference model |
| fit_multimodal_m4 | Fit the M4 latent response-process state model |
| fit_multimodal_trait_irt | Multimodal trait-model convenience wrapper |
| fit_multinomial_transition | Fit a penalized multinomial transition model |
| fit_multiple_response_process_irt | Fit a multiple-response process-IRT reference model |
| fit_nominal_gaze_irt | Nominal/distractor IRT with option-level gaze |
| fit_nonignorable_missing_irt | Create a gated Bayesian nonignorable-missing IRT interface |
| fit_omission_survival_irt | Response/RT/omission survival IRT reference model |
| fit_openmx_adapter | fit openmx adapter |
| fit_openmx_process_model | Fit a user-defined OpenMx process model |
| fit_persistence_gaze_diffusion_irt | Create a gated persistence-augmented gaze-diffusion IRT... |
| fit_process_hmm_irt | Process-state HMM with an IRT response layer |
| fit_process_profile_mixture | Fit exploratory process profiles |
| fit_process_rasch_tree | Fit a process-informed Rasch tree |
| fit_pupil_confound_model | Fit a luminance/fatigue/process confound model for pupil... |
| fit_pupil_event_deconvolution | Fit transparent event-related pupil deconvolution models |
| fit_pupillometryr_adapter | fit pupillometryr adapter |
| fit_response_process_embedding_irt | Fit an IRT response model augmented by sequence embeddings |
| fit_revisit_process_cdm | Fit a revisiting-aware cognitive-diagnosis process workflow |
| fit_seqhmm_adapter | fit seqhmm adapter |
| fit_speed_accuracy_engagement_irt | Speed-accuracy-engagement IRT convenience wrapper |
| fit_strategy_mixture_em | Fit the deterministic multi-start EM baseline |
| fit_strategy_mixture_stan | Fit the probabilistic strategy-mixture engine |
| fit_tam_adapter | fit tam adapter |
| fit_theory_strategy_irt | Fit a theory-constrained strategy mixture |
| fit_traminer_adapter | fit traminer adapter |
| fit_validation_replicate | Fit one model-validation replicate |
| fit_variational_irt | Variational IRT external-engine gate |
| fit_visual_context_irt | Fit an explicit visual-context/testlet IRT model |
| fixation_boundary_uncertainty | Distance to nearest rectangular AOI boundary |
| freeze_eyeprocess_irt_reference | Freeze IRT validation reference summaries |
| freeze_eyeprocess_validation_atlas | Freeze a validation atlas with a reproducibility fingerprint |
| freeze_eyeprocess_validation_evidence | Freeze a complete Milestone #2 evidence bundle |
| freeze_software_paper_evidence | Freeze software-paper evidence to an RDS with a hash |
| freeze_validation_reference | Freeze a compact validation reference for regression testing |
| functional_pupil_basis | Construct a functional basis for pupil trajectories |
| functional_pupil_diagnostics | Diagnose functional pupil model and preprocessing quality |
| functional_pupil_irt_spec | Specify a functional pupil-IRT model |
| gaze_anchored_3pl_alignment | Return the process-alignment table from a gaze-anchored 3PL... |
| gaze_data_quality_profile | Empirical gaze data-quality profile |
| gaze_diffusion_spec | Define a gaze-informed diffusion model |
| gazepoint_analysis_tables | Build person-by-item-by-trial analysis tables |
| gazepoint_irt_tables | Create IRT-ready response and process tables |
| gazepoint_workflow_spec | Specify an integrated Gazepoint downstream workflow |
| gaze_precision_rms_s2s | Estimate RMS successive-sample gaze imprecision |
| gaze_uncertainty_ellipse | Uncertainty ellipse implied by an empirical calibration-error... |
| generalizability_process_study | Generalizability-style variance decomposition for a process... |
| get_irt_model | Retrieve a registered multimodal IRT model |
| grade_model_evidence | Grade model evidence against an explicit validation contract |
| grouped_cv | Evaluate a model with grouped cross-validation |
| grouped_folds | Create grouped cross-validation folds |
| import_benchmark_study | Build an eye dataset from the public benchmark |
| import_eye_bids | Import Eye-Tracking-BIDS physiological recordings |
| incremental_process_validity | Extract incremental process validity |
| init_vendor_corpus | Create or validate a multi-vendor corpus directory |
| inject_aoi_label_noise | Inject AOI label noise |
| inject_calibration_offset | Inject additive gaze calibration offset in coordinate units |
| inject_device_shift | Inject an additive device/site shift in a numeric feature |
| inject_eye_missingness | Inject generic missingness into selected columns |
| inject_pupil_dropout | Inject pupil dropout |
| inject_sampling_jitter | Inject timestamp jitter |
| inject_trial_imbalance | Inject trial/row imbalance by dropping observations |
| irt_compositional_channel | Compositional AOI channel |
| irt_continuous_channel | Continuous/bounded process channel for multimodal IRT |
| irt_count_channel | Count-valued process channel for multimodal IRT |
| irt_functional_channel | Functional trajectory channel |
| irt_model_spec | Define a multimodal IRT model specification |
| irt_nominal_channel | Nominal response/process channel |
| irt_response_channel | Binary/ordinal response channel for multimodal IRT |
| irt_rt_channel | Response-time channel for multimodal IRT |
| irt_sequence_channel | Sequence/process-state channel |
| irt_survival_channel | Survival/event-time channel for multimodal IRT |
| irt_validation_spec | Specify a validation programme for a process-IRT model |
| latent_distribution_stress_test | Stress-test IRT estimators across latent distributions |
| latent_trait_trajectory | Estimate a descriptive continuous-time latent trajectory |
| leave_device_out_validation | Leave device out validation |
| leave_item_out_validation | Leave item out validation |
| leave_session_out_validation | Leave session out validation |
| leave_site_out_validation | Leave site out validation |
| list_irt_models | List registered multimodal IRT models |
| lock_decision_manifest | Lock a decision manifest by content hash |
| map_latent_classes_to_process_profiles | Map supplied latent-class memberships to process summaries |
| measurement_error_budget | Build a non-collapsed measurement-error budget |
| migrate_eye_storage_schema | Migrate a storage schema through an atomic rewrite |
| model_promotion_spec | Specify evidence gates for model promotion |
| model_validation_spec | Specify a model-validation programme |
| model_validation_summary | Summarize model validation |
| multiblock_contributions | Extract multiblock block contributions/coordinates |
| multiblock_person_coordinates | Extract multiblock person coordinates |
| multiblock_variable_coordinates | Extract multiblock variable coordinates |
| multimodal_backend_status | Report multimodal backend availability |
| multimodal_irt_spec | Consolidated multimodal IRT specification |
| multimodal_m2_ablation | Fit M0, M1, and M2 as a response-target ablation sequence |
| multimodal_m2_negative_controls | Generate M2 alignment negative controls |
| multimodal_m2_ppc | Posterior predictive checks for the M2 three-way model |
| multimodal_m2_process_information | Quantify response-target process information in the M0-M2... |
| multimodal_m2_recovery | Run repeated M2 estimator recovery |
| multimodal_m2_spec | M2 response + RT + gaze reference specification |
| multimodal_m3_ablation | Fit the complete M3 response-anchored channel-ablation... |
| multimodal_m3_functional_bridge | Bridge existing functional pupil outputs into the scalar M3... |
| multimodal_m3_negative_controls | Generate M3 multimodal falsification controls |
| multimodal_m3_ppc | Posterior predictive checks for the M3 four-channel model |
| multimodal_m3_process_information | Quantify M3 process information, pupil increment, redundancy... |
| multimodal_m3_recovery | Run M3 parameter-recovery and stress evidence |
| multimodal_m3_spec | M3 response + RT + gaze + pupil specification |
| multimodal_m4_ablation | Plan or fit the focused M3-to-M4 ablation set |
| multimodal_m4_negative_controls | Construct M4 temporal, nuisance, device, and overfitting... |
| multimodal_m4_ppc | Posterior predictive checks for M4 measurement and sequential... |
| multimodal_m4_process_information | Quantify incremental response-target information supplied by... |
| multimodal_m4_recovery | Evaluate deterministic M4 parameter and state recovery |
| multimodal_m4_sensitivity | Plan or run M4 state-count and modelling sensitivity analyses |
| multimodal_m4_spec | Specify M4 trait-conditioned latent response-process states |
| multimodal_m4_state_diagnostics | Summarize M4 latent-state uncertainty and dynamics |
| multimodal_ppc | Posterior predictive checks for multimodal development fits |
| negative_control_concordance | Concordance of multiple negative-control families |
| negative_control_process_test | Negative-control test for an allegedly informative process... |
| object_hash | Hash an R object reproducibly within an R serialization... |
| object_schema | Describe a stable object schema |
| open_eye_storage | Open an eyeprocess storage handle |
| open_partitioned_eye_storage | Open partitioned eye storage |
| option_process_information | Quantify option-process information from a nominal gaze model |
| outcome_blind_feature_audit | Audit whether candidate predictors can be constructed without... |
| outcome_blind_snapshot | Create an outcome-blind data snapshot |
| package_reproducibility_manifest | Create a reproducibility manifest for files and software |
| paper_reproducibility_manifest | Create a compact paper reproducibility manifest |
| partition_eye_storage | Create a partition specification |
| pipeline_failures | Return failed pipeline steps |
| pipeline_result | Extract a pipeline result by step name |
| pipeline_step_status | Pipeline step status table |
| placebo_window_audit | Audit a placebo/pre-event window |
| plot_aoi_transition_matrix | Plot an AOI transition matrix |
| plot_aoi_transition_rank | Plot top AOI transitions by probability/count |
| plot_distractor_information | Plot option-level distractor information |
| plot.eye_adapter_regression_audit | Plot eye adapter regression audit |
| plot.eye_aoi_growth_curve | Plot aoi growth curve diagnostics |
| plot.eye_aoi_trajectory | Plot aoi trajectory diagnostics |
| plot.eye_bayesian_process_dashboard | Plot bayesian process dashboard diagnostics |
| plot.eye_bids_roundtrip | Plot eye bids roundtrip |
| plot.eye_biometric_imputation_sensitivity | Plot biometric imputation sensitivity diagnostics |
| plot.eye_biometric_preflight | Plot biometric preflight diagnostics |
| plot.eye_candidate_item_bank_audit | Plot candidate item bank audit diagnostics |
| plot.eye_compatibility_evidence_matrix | Plot detailed compatibility evidence |
| plot.eye_decision_process_proxy | Plot decision process proxy diagnostics |
| plot.eye_dynamic_irtree | plot eye dynamic irtree |
| plot.eye_dynamic_ppc | plot eye dynamic ppc |
| plot.eye_event_roundtrip_audit | Plot eye event roundtrip audit |
| plot.eye_event_time_irt | Plot eye event time irt |
| plot.eye_functional_pupil_diagnostics | plot eye functional pupil diagnostics |
| plot.eye_functional_pupil_irt | plot eye functional pupil irt |
| plot.eye_functional_pupil_sensitivity | plot eye functional pupil sensitivity |
| plot.eye_gated_process_model | Plot gated process model diagnostics |
| plot.eye_gaze_anchored_3pl_audit | Plot gaze anchored 3pl audit diagnostics |
| plot.eye_gaze_informed_missingness_irt | Plot eye gaze informed missingness irt |
| plot.eye_gpirt | Plot flexible IRF shape diagnostics |
| plot.eye_incremental_information_audit | Plot incremental process-channel information by fold |
| plot.eye_irt_changepoints | Plot detected process changepoints |
| plot.eye_irt_equating | Plot an IRT linking/equating transformation |
| plot.eye_irt_ppc | Plot posterior predictive discrepancy tail probabilities |
| plot.eye_irt_recovery_summary | Plot parameter-recovery bias or RMSE |
| plot.eye_irt_sbc | Plot SBC rank histograms by parameter |
| plot.eye_item_parameter_seed | Plot item parameter seed diagnostics |
| plot.eye_item_reduction_sensitivity | Plot item reduction sensitivity diagnostics |
| plot.eye_joint_gaze_rt_irt | Plot a joint gaze-response-time IRT fit |
| plot.eye_joint_graded_rt_process_irt | Plot a graded response + RT/process fit |
| plot.eye_latent_distribution_comparison | Plot eye latent distribution comparison |
| plot.eye_latent_process_alignment | Plot latent process alignment diagnostics |
| plot.eye_latent_space_irt | Plot a latent-space IRT adapter fit |
| plot.eye_manyfacet_process_irt | Plot many-facet process IRT effects |
| plot.eye_mixture_irt_process | Plot mixture irt process diagnostics |
| plot.eye_model_promotion_audit | plot eye model promotion audit |
| plot.eye_multiblock_process_map | Plot multiblock process map diagnostics |
| plot.eye_nominal_gaze_irt | Plot nominal-response gaze results |
| plot.eye_nonparametric_rasch_audit | Plot nonparametric rasch audit diagnostics |
| plot.eye_omission_survival_irt | Plot omission/not-reached survival IRT diagnostics |
| plot.eye_preaction_process_features | Plot preaction process features diagnostics |
| plot.eye_presentation_accessibility | Plot presentation accessibility diagnostics |
| plot.eye_presentation_fairness_comparison | Plot presentation fairness comparison diagnostics |
| plot.eye_process_anomaly_audit | Plot process anomaly audit diagnostics |
| plot.eye_process_cat_simulation | Plot CAT simulation information accumulation |
| plot.eye_process_channel_ablation | Plot process-channel ablation |
| plot.eye_process_dependent_discrimination | Plot process-dependent discrimination |
| plot.eye_process_drift_audit | Plot process drift audit diagnostics |
| plot.eye_process_external_validity | Plot process external validity diagnostics |
| plot.eye_process_facet_effects | Plot eye process facet effects |
| plot.eye_process_feature_blocks | Plot process feature blocks diagnostics |
| plot.eye_process_g_study | Plot process-measure variance components |
| plot.eye_process_hmm_irt | Plot a process-HMM IRT fit |
| plot.eye_process_local_dependence_audit | Plot process/local-dependence diagnostics |
| plot.eye_process_negative_control | Plot a process-channel negative-control distribution |
| plot.eye_process_person_fit | Plot process person-fit discrepancies |
| plot.eye_process_profile_mixture | Plot process profile mixture diagnostics |
| plot.eye_process_rasch_tree | Plot process rasch tree diagnostics |
| plot.eye_process_windows | Plot process windows diagnostics |
| plot.eye_process_window_sensitivity | Plot process window sensitivity diagnostics |
| plot.eye_pupil_confound_model | Plot pupil confound model diagnostics |
| plot.eye_pupil_deconvolution | Plot pupil deconvolution diagnostics |
| plot.eye_pupil_fatigue_drift | Plot pupil fatigue drift diagnostics |
| plot.eye_pupil_frequency_features | Plot pupil frequency features diagnostics |
| plot.eye_pupil_frequency_stability | Plot pupil frequency stability diagnostics |
| plot.eye_roundtrip_loss_audit | plot eye roundtrip loss audit |
| plot.eye_sbc_audit | Plot SBC audit summaries |
| plot.eye_semantic_roundtrip | Plot semantic round-trip fidelity |
| plot.eye_signal_filter_audit | Plot signal filter audit diagnostics |
| plot.eye_storage_benchmark | plot eye storage benchmark |
| plot.eye_strategy_aoi_sensitivity | plot eye strategy aoi sensitivity |
| plot.eye_streaming_score | Plot streaming score diagnostics |
| plot.eye_transition_diagnostics | plot eye transition diagnostics |
| plot.eye_validation_bundle | Plot validation bundle diagnostics |
| plot.eye_vendor_compatibility_matrix | plot eye vendor compatibility matrix |
| plot.eye_vendor_semantic_validation | Plot eye vendor semantic validation |
| plot.eye_visual_context_irt | Plot visual context irt diagnostics |
| plot_gazepoint_workflow | Generate the complete Gazepoint workflow plot suite |
| plot_interval_coverage | Plot interval coverage |
| plot_irf_uncertainty | Plot uncertainty for flexible item response functions |
| plot_parameter_recovery | Plot parameter recovery |
| plot_person_item_space | Plot person/item latent-space coordinates |
| plot_process_changepoint | Plot detected process change points |
| plot_process_channel_ablation_delta | Plot channel-ablation delta from a full/reference model |
| plot_process_feature_stability | Plot process-feature stability across resamples/splits |
| plot_process_window_sensitivity | Explicit wrapper for process-window sensitivity plotting |
| plot_pupil_activity_sensitivity | Plot pupil activity sensitivity to window length |
| plot_pupil_activity_windows | Plot pupil activity features across windows/groups |
| plot_pupil_band_power | Plot pupil low/high-band power summaries |
| plot_pupil_components | Plot tonic/phasic pupil components |
| plot_pupil_preprocessing_audit | Plot raw-to-processed pupil preprocessing stages |
| plot_pupil_spectrum | Plot a pupil-signal power spectrum |
| plot_sbc_rank | Plot SBC rank histograms |
| plot_validation_failures | Plot validation failure rates |
| plot_validation_runtime | Plot validation runtime |
| posterior_predictive_discrepancies | Posterior predictive discrepancy table |
| posterior_sbc_contract | Define a posterior-SBC replication contract |
| preaction_process_features | Build pre-action process features |
| predict_aoi_trajectory | Predict from an AOI growth curve |
| predict.eye_censored_normal_process_irt | Predict expected bounded response from a censored-normal... |
| predict.eye_multinomial_transition | Predict destination-state probabilities |
| predict_item_parameter_priors | Predict pre-pilot item-parameter priors |
| predict_theta_at_time | Predict a latent trait at arbitrary times |
| preflight_decisions | Extract pre-flight decisions |
| preflight_exclusion_manifest | Create an explicit pre-flight exclusion/review manifest |
| preflight_failures | Extract pre-flight failures/review cases |
| preflight_passed | Extract pre-flight passes |
| prepare_dynamic_irtree_data | Prepare ordered transition data for dynamic IRTree models |
| prepare_functional_pupil_data | Prepare aligned, corrected functional pupil data |
| prepare_gaze_diffusion_data | Prepare joint accuracy-response-time data |
| prepare_multimodal_irt_data | Prepare a canonical multimodal person-item-trial measurement... |
| prepare_strategy_mixture_data | Prepare data for a strategy-mixture model |
| prepare_structured_unstructured_process_features | Prepare leakage-safe structured/unstructured process... |
| preprocessing_multiverse | Run a preprocessing or AOI multiverse |
| print.eye_benchmark_reproduction | print eye benchmark reproduction |
| print.eye_benchmark_study | print eye benchmark study |
| print.eye_benchmark_validation | print eye benchmark validation |
| print.eye_diffusion_diagnostics | print eye diffusion diagnostics |
| print.eye_diffusion_identification_study | print eye diffusion identification study |
| print.eye_dynamic_irtree | print eye dynamic irtree |
| print.eye_dynamic_ppc | print eye dynamic ppc |
| print.eye_dynamic_recovery | print eye dynamic recovery |
| print.eye_engine_adapter_result | print eye engine adapter result |
| print.eye_functional_pupil_data | print eye functional pupil data |
| print.eye_functional_pupil_diagnostics | print eye functional pupil diagnostics |
| print.eye_functional_pupil_irt | print eye functional pupil irt |
| print.eye_functional_pupil_sensitivity | print eye functional pupil sensitivity |
| print.eye_functional_scalar_comparison | print eye functional scalar comparison |
| print.eye_gated_process_model | Print a gated process model object |
| print.eye_gaze_diffusion_data | print eye gaze diffusion data |
| print.eye_gaze_diffusion_irt | print eye gaze diffusion irt |
| print.eye_gaze_diffusion_spec | print eye gaze diffusion spec |
| print.eye_irt_evidence_grade | Print eye irt evidence grade |
| print.eye_irt_model_spec | Print a multimodal IRT model specification |
| print.eye_irt_validation_spec | Print eye irt validation spec |
| print.eye_model_contract_validation | print eye model contract validation |
| print.eye_model_promotion_audit | print eye model promotion audit |
| print.eye_multinomial_transition | print eye multinomial transition |
| print.eye_partitioned_storage | print eye partitioned storage |
| print.eye_partition_spec | print eye partition spec |
| print.eye_process_drift_spec | Print a process drift spec object |
| print.eye_process_negative_control | Print eye process negative control |
| print.eye_process_preflight_spec | Print a process preflight spec object |
| print.eye_process_window_spec | Print a process window spec object |
| print.eye_redaction_result | print eye redaction result |
| print.eye_roundtrip_loss_audit | print eye roundtrip loss audit |
| print.eye_strategy_data | print eye strategy data |
| print.eye_strategy_manipulation_validation | print eye strategy manipulation validation |
| print.eye_theory_strategy_irt | print eye theory strategy irt |
| print.eye_theory_strategy_spec | print eye theory strategy spec |
| print.eye_transition_design | print eye transition design |
| print.eye_transition_diagnostics | print eye transition diagnostics |
| print.eye_validation_bundle | Print a validation bundle object |
| print.eye_validation_case_fingerprint | print eye validation case fingerprint |
| print.eye_validation_collection | print eye validation collection |
| print.eye_validation_completion_audit | print eye validation completion audit |
| print.eye_validation_job_plan | print eye validation job plan |
| print.eye_validation_run | print eye validation run |
| print.eye_vendor_case | print eye vendor case |
| print.eye_vendor_compatibility_matrix | print eye vendor compatibility matrix |
| print.eye_vendor_schema_contract | Print eye vendor schema contract |
| print.eye_vendor_semantic_comparison | print eye vendor semantic comparison |
| print.eye_visual_context_registry | Print a visual context registry object |
| probabilistic_aoi_assignment | Probabilistic AOI assignment under empirical calibration... |
| process_anomaly_distance | Extract multivariate process anomaly distances |
| process_bland_altman | Bland-Altman repeatability summary for two sessions |
| process_channel_ablation | Ablate process channels under a common out-of-sample... |
| process_criterion_associations | Extract process-criterion associations |
| process_dependent_discrimination_audit | Audit process-dependent item discrimination |
| process_dif_nuisance_surrogate | Construct a process-data nuisance surrogate for DIF analysis |
| process_drift_alerts | Extract drift alerts |
| process_drift_spec | Specify a process-deployment drift audit |
| process_feature_blocks | Define conceptual process-feature blocks |
| process_feature_family_registry | Registry of process-feature families and interpretation... |
| process_feature_stability | Summarize process-feature stability across repeated analyses |
| process_feature_time_provenance | Declare temporal provenance for process features |
| process_icc | Absolute-agreement ICC(A,1) for repeated process measures |
| process_information | Quantify incremental process information |
| process_item_information | 2PL response item information |
| process_measure_card | Return a one-measure process card |
| process_measure_coverage | Process-measure coverage for an observed dataset |
| process_measure_guardrails | Process-measure guardrail table |
| process_measure_lineage | Process-measure lineage table |
| process_measure_registry | Unified process-measure registry |
| process_measure_units | List units used by registered process measures |
| process_negative_control_permute | Permutation negative control |
| process_negative_control_shift | Temporal-shift negative control |
| process_ngram_features | N-gram features from process sequences |
| process_null_benchmark | Compare an observed effect against a negative-control null... |
| process_person_fit | Joint response-process person-fit diagnostic |
| process_preflight_spec | Specify a biometric process pre-flight gate |
| process_profile_probabilities | Extract process-profile probabilities |
| process_profile_summary | Summarize process profiles |
| process_reliability_profile | Test-retest process reliability profile |
| process_residual_map | Return person/item latent-space coordinates |
| process_sensitivity_grid | Construct an explicit process-analysis sensitivity grid |
| process_sequence_embedding | Low-dimensional embedding of response-process sequences |
| process_state_occupancy | Summarize HMM state occupancy |
| process_state_transition_summary | Summarize HMM process-state transitions |
| process_temporal_stability | Pairwise temporal stability across sessions |
| process_validation_design | Define an empirical process-validation design |
| process_window_spec | Specify temporal process windows |
| promote_irt_model | Promote an IRT model after evidence gates are met |
| promote_vendor_support | Promote a case support level only when evidence is supplied |
| propagate_calibration_uncertainty | Propagate empirical calibration uncertainty around gaze... |
| provenance_edge_table | Build a provenance edge table |
| provenance_lineage_table | Build a provenance lineage node table |
| prune_validation_checkpoints | Remove obsolete or corrupt validation checkpoints |
| public_validation_corpus | Public validation-corpus registry |
| pupil_activity_index | Compute a transparent pupil activity index |
| pupil_band_power | Compute pupil signal power in a frequency band |
| pupil_baseline_sensitivity | Evaluate pupil baseline-window sensitivity |
| pupil_confound_effects | Extract pupil confound-model effects |
| pupil_event_effects | Extract event effects from pupil deconvolution |
| pupil_event_regressor | Build an event-locked pupil regressor |
| pupil_frequency_features | Extract pupil frequency-domain and activity features by group |
| pupil_latency_sensitivity | Pupil latency estimator sensitivity and resolvability audit |
| pupil_preprocessing_grid | Create a preprocessing sensitivity grid for pupil analysis |
| pupil_preprocessing_sensitivity | Run functional pupil preprocessing sensitivity analysis |
| pupil_response_kernel | Canonical gamma-shaped pupil response kernel |
| pupil_unit_fidelity_audit | Pupil-unit semantic-fidelity audit |
| pupil_velocity_activity | Derivative-based pupil activity magnitude |
| quantify_process_leakage | Quantify leakage from row-wise rather than grouped validation |
| query_eye_storage | Query partitioned eye storage lazily where possible |
| raven_reproduction_spec | Specify a published Raven strategy-model reproduction |
| read_api_lifecycle_registry | Read API lifecycle registry from CSV |
| read_benchmark_table | Read a benchmark table |
| read_decision_manifest | Read a decision manifest written by eyeprocess |
| read_eyeprocess_validation_evidence | Read and verify a frozen evidence bundle |
| read_reproducibility_fingerprint | Read a reproducibility fingerprint |
| read_validation_job_manifest | Read a validation manifest |
| read_validation_scenario_manifest | Read a validation scenario manifest |
| read_vendor_registry | Read the multi-vendor case registry |
| recalibrate_after_changepoint | Iteratively detect, clean, and recalibrate after process... |
| recommended_validation_replications | Approximate simulation replications needed for a target Monte... |
| redact_validation_case | Redact a validation case without inventing replacement data |
| register_eye_api_status | Add or update API lifecycle metadata without global mutation |
| register_irt_model | Register a multimodal IRT model |
| register_process_measure | Add a process measure to a registry without global mutation |
| register_validation_case | Register an independent validation case |
| register_vendor_semantics | Register vendor-field semantics |
| reporting_guideline_audit | Audit reporting-guideline coverage |
| resume_eye_pipeline | Resume a governed pipeline from a prior run |
| resume_validation_jobs | Resume incomplete or failed validation jobs |
| roundtrip_eye_bids | Execute and audit an Eye-Tracking-BIDS round trip |
| run_benchmark_reproduction | Derive reproducible benchmark summaries |
| run_eye_benchmark | Run a computational scaling benchmark |
| run_eye_pipeline | Run a governed eyeprocess pipeline |
| run_eyeprocess_equateirt | Run a named equateIRT linking/equating function without... |
| run_eyeprocess_irt_ability_sbc | Run simulation-based calibration for known-item IRT ability... |
| run_eyeprocess_irt_recovery | Run IRT parameter recovery with the exact mirt engine |
| run_eyeprocess_mirtcat | Run a mirtCAT adaptive-testing workflow without fallback... |
| run_eyeprocess_stress_evidence | Execute a declared measurement-stress evidence plan |
| run_eyeprocess_validation_program | Run the complete validation-release programme |
| run_gazepoint_workflow | Run the complete Gazepoint downstream workflow |
| run_model_validation | Run parameter-recovery, coverage, and misspecification... |
| run_posterior_sbc | Run posterior simulation-based calibration from an explicit... |
| run_process_negative_controls | Run repeated process negative controls |
| run_process_sensitivity | Run an explicit process-analysis multiverse |
| run_process_validation | Run an empirical process-validation programme |
| run_raven_reproduction | Execute a licensed published-model reproduction |
| run_sbc | Run generic simulation-based calibration |
| run_validation_jobs | Run validation jobs with checkpointing and deterministic... |
| sbc_ecdf_deviation | ECDF deviation summary for SBC ranks |
| sbc_rank_diagnostics | Build SBC rank diagnostics |
| sbc_summary | Summarize simulation-based calibration |
| score_partial_response_pattern | Score a partial response pattern from a calibrated mirt model |
| score_response_stream | Score a response stream cumulatively |
| select_next_item_process | Select the next item using response/process utility |
| semantic_fidelity_spec | Semantic fidelity specification |
| semantic_loss_map | Convert a semantic round-trip audit into a loss map |
| semantic_roundtrip_audit | Audit a complete semantic round trip |
| sensitivity_branch_fingerprint | Stable fingerprint of a sensitivity branch |
| sensitivity_decision_leverage | Decision leverage of each analytical choice |
| sensitivity_fragility_index | Fragility index across analysis specifications |
| sensitivity_multiverse_manifest | Machine-readable multiverse manifest |
| sensitivity_rank_stability | Rank stability across specifications |
| sensitivity_significance_stability | Significance-decision stability across specifications |
| sensitivity_sign_stability | Effect-sign stability across specifications |
| sensitivity_threshold_stability | Substantive-threshold stability across specifications |
| sequence_interoperability | Convert scanpaths to process/sequence package contracts |
| session_facet_effects | Extract session facet effects |
| simulate_advanced_process_data | Simulate advanced response-process data |
| simulate_dynamic_irtree_data | Simulate observed dynamic-state transitions |
| simulate_eyeprocess_catr | Run a catR adaptive-testing simulation without fallback... |
| simulate_eyeprocess_irt_binary | Simulate dichotomous IRT responses with optional local... |
| simulate_from_model | Simulate data from a model or registered model specification |
| simulate_gaze_diffusion_data | Simulate a hierarchical gaze-diffusion study |
| simulate_irt_model | Simulate from a registered multimodal IRT model |
| simulate_multimodal_irt | Simulate multimodal IRT process data |
| simulate_multimodal_m2 | Simulate from the M2 response + RT + gaze generative model |
| simulate_multimodal_m3 | Simulate the M3 response + RT + gaze + pupil generative model |
| simulate_multimodal_m4 | Simulate M4 multimodal sequential measurement data |
| simulate_presentation_variants | Simulate pre-registered presentation variants for review |
| simulate_process_cat | Simulate a simple process-aware CAT policy |
| simulate_process_validation_data | Simulate a generic multimodal validation dataset with known... |
| simulate_strategy_mixture_data | Simulate a theory-defined strategy-mixture study |
| simulation_based_calibration | Run simulation-based calibration |
| simulation_rank_statistic | Compute a simulation-based calibration rank statistic |
| software_paper_claim_matrix | Create or normalize a software-paper claim matrix |
| software_paper_coverage | Compute descriptive evidence coverage |
| software_paper_evidence_bundle | Construct a software-paper evidence bundle |
| software_paper_gap_analysis | Identify gaps in a software-paper evidence bundle |
| software_paper_readiness | Descriptive software-paper readiness audit |
| software_paper_validation_table | Summarise validation evidence for a software paper |
| specification_coverage | Fraction of planned specifications successfully evaluated |
| specification_curve_data | Prepare ordered specification-curve data |
| split_half_process_reliability | Split-half reliability for a trial-level process measure |
| split_validation_plan | Split a validation plan into independent chunks |
| storage_transaction_manifest | Return the transaction manifest |
| strategy_aoi_sensitivity | Assess sensitivity to alternative AOI feature definitions |
| strategy_classification_uncertainty | Quantify strategy-classification uncertainty |
| strategy_label_switching_diagnostics | Diagnose label stability across multiple starts |
| strategy_posterior_probabilities | Posterior strategy probabilities |
| streaming_score_history | Extract streaming score history |
| stress_test_latent_distribution | Stress test latent distribution |
| stress_test_local_dependence | Stress test local dependence |
| stress_test_missingness | Stress test missingness |
| stress_test_misspecification | Run a generic misspecification stress-test grid |
| stress_test_preprocessing | Stress test preprocessing |
| stress_test_process_pipeline | Stress-test an analysis under explicit synthetic corruptions |
| stress_test_speededness | Stress test speededness |
| stress_test_summary | Summarise stress-test metrics |
| stress_tolerance_frontier | Identify the empirical stress frontier for a metric |
| structural_transition_mask | Define structural-zero and allowed transition masks |
| summarise_eye_benchmark | Summarise benchmark timing and memory by problem size |
| summarise_eyeprocess_stress_evidence | Summarise executed measurement-stress evidence |
| summarise_process_negative_controls | Summarise process negative controls |
| summarise_process_sensitivity | Summarise process sensitivity results |
| summarise_process_validation | Summarise a process-validation result |
| summarise_validation_acceptance | Summarise an acceptance matrix |
| summarize_parameter_recovery | Summarise parameter recovery |
| summarize_process_windows | Summarize extracted process windows |
| summary.eye_validation_bundle | Summarize a validation bundle object |
| summary.eye_validation_job_plan | summary eye validation job plan |
| synthetic_corruption_plan | Define synthetic measurement corruptions for stress testing |
| theory_strategy_spec | Define a theory-constrained strategy-mixture model |
| timestamp_fidelity_audit | Timestamp semantic-fidelity audit |
| transition_residual_diagnostics | Compute transition residual diagnostics |
| update_person_score | Update a partial person score with one new response |
| upgrade_eye_dataset | Upgrade a legacy eye dataset |
| upgrade_eyeprocess_model | Upgrade a legacy eyeprocess model |
| validate_against_reference | Compare a validation result with a frozen reference |
| validate_benchmark_study | Validate benchmark integrity and relational constraints |
| validate_bids_eye_semantics | Validate BIDS eye-tracking semantics |
| validate_decision_manifest | Validate a research decision manifest |
| validate_engine_adapter | Validate an external-engine adapter contract |
| validate_eye_pipeline | Validate a governed eyeprocess pipeline |
| validate_eyeprocess_external_irt_fit | Validate that an external IRT fit used the requested engine |
| validate_eyeprocess_irt_item_bank | Validate an adaptive IRT item bank |
| validate_eyeprocess_irt_model_spec | Validate an eyeprocess IRT model specification |
| validate_eyeprocess_joint_process_irt_spec | Validate a joint process IRT specification |
| validate_eyeprocess_validation_plan | Validate a validation-evidence plan |
| validate_eye_prov_graph | Validate a provenance graph |
| validate_eye_storage_metadata | Validate storage metadata and partition fingerprints |
| validate_feature_availability | Validate feature availability against an analysis cutoff |
| validate_gazepoint_workflow | Validate an integrated Gazepoint workflow result |
| validate_hed_event_semantics | Minimal HED annotation audit for event tables |
| validate_irt_model | Validate a registered multimodal IRT model |
| validate_latent_space_process_similarity | Validate latent-space proximity against process similarity |
| validate_model_object | Validate a fitted model against the stable model contract |
| validate_multimodal_irt | Validate a multimodal IRT development object |
| validate_multimodal_m2 | Validate an M2 fit or simulation |
| validate_multimodal_m3 | Validate an M3 simulation or fitted four-channel model |
| validate_multimodal_m4 | Validate M4 data, computation, state behavior, and evidence |
| validate_process_measure_registry | Validate a process-measure registry |
| validate_process_validation_design | Validate a process-validation design |
| validate_process_windows | Validate a process-window representation |
| validate_strategy_manipulation | Validate strategy posteriors against an experimental... |
| validate_vendor_semantics | Validate imported data against a vendor semantic contract |
| validate_vendor_timestamp_semantics | Validate vendor-specific timestamp semantics |
| validation_acceptance_matrix | Evaluate a table against named validation rules |
| validation_acceptance_rule | Define a validation acceptance rule |
| validation_bundle_manifest | Create a machine-readable validation manifest |
| validation_calibration_summary | Summarize prediction calibration |
| validation_condition_id | Return stable validation condition identifiers |
| validation_condition_ranking | Rank validation conditions by a transparent robustness score |
| validation_coverage_table | Interval-coverage table |
| validation_evidence_levels | Detailed validation evidence levels |
| validation_evidence_matrix | Create a model-by-evidence validation matrix |
| validation_failure_profile | Failure profile for a validation programme |
| validation_failure_summary | Summarize convergence and execution failures |
| validation_failure_taxonomy | Classify common estimator failures without hiding the... |
| validation_job_plan | Create a deterministic validation job plan |
| validation_ladder | Build a measurement-to-generalization validation ladder |
| validation_mcse | Monte Carlo standard errors for validation metrics |
| validation_mcse_profile | Estimate Monte Carlo uncertainty for validation summaries |
| validation_recovery_summary | Summarize parameter recovery |
| validation_recovery_table | Parameter-recovery table |
| validation_replication_budget | Compute a replication budget from a target MCSE |
| validation_report | Render a conservative validation report |
| validation_robustness_score | Overall validation robustness score |
| validation_runtime_summary | Summarize validation runtime and checkpoint scale |
| validation_sbc_summary | Summarize simulation-based calibration ranks |
| validation_scenario_manifest | Create a scenario manifest for frozen validation work |
| validation_seed | Allocate a deterministic validation seed |
| validation_summary_mcse | Monte Carlo standard-error diagnostics for validation... |
| validation_thresholds | Specify completion and scientific-promotion thresholds |
| vendor_schema_contract | Declare a vendor semantic schema contract |
| vendor_validation_spec | Specify multi-vendor empirical validation requirements |
| verify_decision_manifest_lock | Verify that a locked manifest has not changed |
| verify_eyeprocess_validation_atlas | Verify a frozen validation atlas |
| verify_eyeprocess_validation_evidence | Verify the integrity hash of a frozen evidence bundle |
| verify_outcome_blind_snapshot | Verify an outcome-blind snapshot has not changed |
| verify_reproducibility_fingerprint | Verify an internally stored fingerprint hash |
| verify_reproducibility_manifest | Verify a reproducibility manifest |
| visual_context_registry | Build an item-to-visual-context registry |
| write_advanced_model_evidence_report | Write an advanced-model evidence report |
| write_api_lifecycle_registry | Write API lifecycle registry to CSV |
| write_benchmark_data_dictionary | Write the benchmark data dictionary |
| write_decision_manifest | Write a decision manifest |
| write_eye_pipeline_report | Write a conservative pipeline report |
| write_eyeprocess_validation_evidence | Write a frozen evidence bundle |
| write_eyeprocess_validation_report | Write a compact Markdown validation report |
| write_eye_storage | Write an eye dataset to RDS or Arrow/Parquet storage |
| write_eye_targets_template | Write an explicit '_targets.R' template from a governed... |
| write_gazepoint_workflow_report | Write a reproducible Gazepoint workflow report |
| write_model_promotion_report | Write a model-promotion report |
| write_partitioned_eye_storage | Write an eye dataset as atomic partitioned storage |
| write_prov_dot | Return Graphviz DOT for a provenance graph |
| write_reporting_guideline_report | Write a reporting-guideline audit report |
| write_reproducibility_fingerprint | Write a reproducibility fingerprint |
| write_software_paper_evidence | Write a human-readable software-paper evidence report |
| write_software_paper_reproduction | Write a complete software-paper reproduction scaffold |
| write_software_paper_scaffold | Write a methodological software-paper scaffold |
| write_validation_job_manifest | Write a machine-readable validation manifest |
| write_validation_release_report | Write a validation release report |
| write_validation_report | Write a validation report to disk |
| write_validation_scenario_manifest | Write a validation scenario manifest |
| write_vendor_case_report | Write a vendor case evidence report |
| write_vendor_registry | Write the multi-vendor case registry |
| write_vendor_validation_report | Write a multi-vendor validation report |
