Specify evidence required to promote advanced model interfaces

Usage

advanced_model_evidence_spec(
  models = c("fit_joint_process_model", "fit_shared_process_factor",
    "fit_strategy_mixture", "fit_process_irt", "fit_pupil_informed_irt",
    "fit_multimodal_irt", "fit_dynamic_aoi_model", "fit_gaze_weighted_choice",
    "fit_dynamic_irtree", "fit_joint_functional_pupil_irt", "fit_theory_strategy_irt",
    "fit_gaze_diffusion_irt"),
  require_recovery = TRUE,
  require_calibration = TRUE,
  require_misspecification = TRUE,
  require_grouped_validation = TRUE,
  require_engine_equivalence = TRUE,
  require_empirical_reproduction = TRUE,
  require_sensitivity = TRUE
)

Arguments

models: Advanced model function names.
require_recovery: Require passing parameter-recovery evidence.
require_calibration: Require simulation-based calibration evidence.
require_misspecification: Require evidence that prespecified failure scenarios are detected.
require_grouped_validation: Require grouped out-of-sample validation.
require_engine_equivalence: Require comparison with a benchmark engine.
require_empirical_reproduction: Require a licensed empirical reproduction.
require_sensitivity: Require a multi-specification preprocessing/AOI sensitivity analysis.

Value

An `eye_advanced_evidence_spec`.