Article library¶
All 59 canonical gp3bayes 0.5.0 articles are available as Python-facing guides. They are grouped by task so you can enter through the problem you are trying to solve rather than a flat filename list.
Start here · core workflows¶
The shortest route from a declared design to an inspectable Bayesian workflow.
- End-to-End Hierarchical Binary Workflow
- End-to-End Hierarchical Lognormal Duration Workflow
- A Stable Unified Workflow API
- Specification Closure: Strict Readiness and Governed Validation
- First-Class Estimands and Sensitivity Workflows
- Transformation Replay and Detailed Posterior Predictive Checks
- Pre-fit Design-Support Diagnostics
Posterior & predictive evidence¶
Diagnostics, prediction, calibration, uncertainty, hierarchical effects, and PSIS-LOO.
- Sampling Diagnostics and Conservative Decisions
- Advanced Predictive Diagnostics
- Posterior Exploration and Publication Graphics
- Prediction, Calibration, and Scoring
- Prediction Contrasts, Rankings, and Groups
- Prediction Profiles, Surfaces, and Contrast Profiles
- Predictive Distribution and Calibration Uncertainty
- Functional Dynamics and Predictive Calibration
- Hierarchical Effects and Predictive Uncertainty
- Hierarchical Effect and Variance Atlases
- LOO Influence and Predictive Model Comparison
- Pointwise LOO Influence Atlases
- Grouped PSIS-LOO Influence
- Declared Priors versus Fitted Posteriors
Sensitivity, recovery & reproducibility¶
Stress-test the analysis, recover known truths, and preserve a reproducible evidence trail.
- Prior Sensitivity and Simulation-Based Recovery
- Sensitivity Atlases
- Unified Sensitivity Suites and Evidence Inventories
- Parameter Recovery Diagnostics for Publication
- Simulation-Based Calibration Diagnostics
- Analysis Manifests and Reproducible Bayesian Workflows
- Pathological Simulation Scenarios
- A Reproducible 0.2.0 Release Case Study
Backends, governance & publication¶
Portability, backend checks, model cards, evidence graphics, publication bundles, and quality contracts.
- Backend Portability and Installation
- Backend Reliability, Parity and Object Schemas
- Optional Bayesian Backend Installation
- Advanced Optional Bayesian Workflows
- Computational Governance and Model Cards
- Model Cards and Reporting Inventories
- Evidence Graphics and Governance
- Publication-Ready Analysis Bundles
- Publication Registries and Diagnostic Dashboards
- End-to-End Evidence and Publication Showcase
- Complete Public API Map
- Quality Hardening and Failure Contracts
Dynamic pupillometry · foundations¶
Measurement context, preparation, model fitting, trajectories, temporal validation, and Gazepoint interoperability.
- Bayesian dynamic pupillometry: governed foundation
- Preparing and auditing pupil time courses
- Fitting hierarchical pupil time-course models
- Posterior pupil trajectories and declared estimands
- Pupil posterior predictive checks and temporal diagnostics
- Validation for temporally dependent pupil data
- Baseline, gaze/PFE, and luminance sensitivity
- Gazepoint pupil-data interoperability
- Synthetic Gazepoint pupillometry case study
Dynamic pupillometry · advanced¶
Advanced dynamics, binocular models, Gaussian processes, ARMA, robust distributions, missingness, and model comparison.
- Advanced Dynamic Pupillometry in gp3bayes 0.5
- Joint Binocular Pupil Models
- Gaussian-Process Pupil Trajectories
- Bounded ARMA and Temporal Diagnostics
- Robust and Distributional Pupil Models
- Measurement Uncertainty and Missing Pupil Data
- Experimental Interpretable Pupil Response Shape
- Governed Predictive Model Comparison
- Synthetic Advanced Pupillometry Gallery
Supplementary visual galleries¶
These are additional Python visual guides and are not counted among the frozen 59 canonical gp3bayes articles.
Looking for a function?¶
Use the API reference hub to browse the public API by module, or use the site search in the header.