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Bounded ARMA and Temporal Diagnostics

Python-facing port of arma-and-temporal-diagnostics.Rmd from the frozen R gp3bayes 0.5.0 reference. The statistical and governance framing below follows the canonical vignette; executable Python workflows use the mapped APIs listed later.

Audit first; do not select an order from a plot

The observed ACF can reflect residual dependence, misspecified mean trajectories, design structure, preprocessing, or combinations of these. gp3bayes therefore treats the audit as descriptive evidence rather than an order-selection algorithm.

Governed ARMA orders

Orders are bounded to AR(3)/MA(2). The common shortcuts are available directly in the model specification.

Post-fit residual comparison

Residual spectra are deliberately descriptive. Peaks are not interpreted as cognitive or physiological rhythms by gp3bayes.

Python API mapping

  • gp3bayespy.audit_pupil_temporal_dependence
  • gp3bayespy.compare_pupil_autocorrelation
  • gp3bayespy.create_pupil_arma_spec
  • gp3bayespy.fit_advanced_pupil_model_backend
  • gp3bayespy.plot_pupil_autocorrelation_comparison
  • gp3bayespy.plot_pupil_residual_spectrum
  • gp3bayespy.plot_pupil_temporal_dependence
  • gp3bayespy.pupil_autocorrelation_table
  • gp3bayespy.pupil_residual_spectrum
  • gp3bayespy.simulate_advanced_pupil_timecourse
  • gp3bayespy.specify_advanced_pupil_timecourse_model

Python usage

import gp3bayespy as gp

# All functions listed above are available from the package root.
# Use help(gp.<function>) or the API reference for the exact Python signature.