Nothing
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE) library(eyeprocess)
pre <- preaction_process_features(samples) proxy <- addm_glam_proxy_features( samples, target_aoi = "target", distractor_aoi = "distractor", action_aoi = "button" ) plot(pre) plot(proxy)
These are aDDM/GLAM-inspired feature summaries. They are not fitted drift rate, gaze-discount, or decision-threshold parameters.
process_feature_family_registry() assign_process_feature_family(c("pupil_peak", "aoi_entropy", "valid_gaze_prop")) process_feature_stability(repeated_importance_table)
fit_kde_latent_distribution_irt(response_matrix) fit_persistence_gaze_diffusion_irt(process_data) fit_nonignorable_missing_irt(missingness_data) fit_crossclassified_process_irt_mhrm(crossclassified_data)
Without an explicit validated external engine these functions return a gated model contract rather than silently substituting a simpler model.
repr <- prepare_structured_unstructured_process_features( structured_features, unstructured = sequence_data, fold = "fold_id" )
The representation contract states that learned scaling, vocabulary, embedding, feature selection, and similar operations must be fitted inside training folds only.
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