# gp3bayes 0.5.0

## Advanced dynamic and measurement-aware Bayesian pupillometry

* Adds an additive advanced pupil-model specification layer while preserving the frozen 0.4 public API.
* Adds Gaussian and Student-t observation models with constant, condition-dependent, time-dependent, and condition-by-time residual scale specifications.
* Adds bounded governed residual temporal dependence through AR(1), AR(2), ARMA(1,1), and explicit ARMA specifications constrained to p <= 3 and q <= 2.
* Adds governed Gaussian-process trajectories with Matérn 3/2, Matérn 5/2, and exponentiated-quadratic kernels; approximate Hilbert-space GP bases are the scalable default and exact GP requests are subject to a complexity audit.
* Adds explicit known measurement-uncertainty declarations for pupil responses and covariates and MAR-oriented joint missing-value models without automatic interpolation.
* Adds joint binocular pupil preparation, multivariate modelling, residual eye correlation, eye-difference estimands, and agreement summaries without requiring upstream eye averaging.
* Adds governed PSIS-LOO, exact K-fold, predictive model weights, and explicit leave-future-out validation plans. Model comparison never chooses a substantive winner automatically.
* Adds an experimental nonlinear pupil response-shape model with interpretable baseline, amplitude, onset, rise, duration, and decay parameters.
* Adds posterior temporal derivative, dynamic condition-contrast, and prespecified threshold-duration estimands without automatic onset, changepoint, or favorable-window detection.
* Adds computational-budget, design-support/identifiability, temporal-dependence, measurement, missingness, predictive-calibration, and advanced-fit diagnostics.
* Adds posterior residual-scale, GP hyperparameter, residual-spectrum, model-card, sensitivity-suite, and publication-oriented tables and graphics.
* Adds deterministic advanced and binocular simulation utilities with truth stored separately from analysis data.
* Adds backend-free examples, plotting galleries, focused tests, and eleven advanced pupillometry articles.

## Governance boundaries

* gp3bayes 0.5 does not interpolate or otherwise preprocess missing pupil samples automatically.
* MAR-oriented missing-data modelling is assumption-conditional and does not establish that MAR is true.
* Student-t robustness does not mark individual observations as invalid outliers.
* Predictive comparison, stacking weights, temporal derivatives, threshold durations, and nonlinear response parameters do not establish model adequacy, causality, or cognitive/physiological states.
* MNAR models, overlapping-event deconvolution, automatic changepoint detection, multimodal psychophysiological latent-state inference, automated model search, and automatic cognitive-state inference remain outside the 0.5 scope.

# gp3bayes 0.4.0.9000

### Bayesian dynamic pupillometry foundation

* Adds a first-class, vendor-neutral pupil time-course contract with verified Gazepoint schema inspection and explicit unit handling.
* Adds deterministic pupil simulation, governed preparation, readiness and measurement-context audits without silent blink interpolation, smoothing, PFE correction, luminance correction, or exclusion.
* Adds a restricted Gaussian hierarchical pupil time-course family with smooth or linear trajectories, optional condition-specific trajectories, participant/item hierarchy, declared covariates, scale-aware priors, and an optional guarded AR(1) structure.
* Adds backend-portable full-MCMC fitting through `brms` with `rstan` or `cmdstanr`, plus prior-predictive planning/execution under the same closed specification.
* Adds posterior pupil trajectories, declared-window means, AUC, peak response, peak latency, condition contrasts, threshold probabilities, PPCs, temporal diagnostics, target-specific grouped/future validation, and declared sensitivity scenarios.
* Adds publication tables, `ggplot2` graphics, nine pupillometry articles, focused failure-contract tests, a frozen 0.4.0.9000 API manifest, and a dedicated development audit.
* Pupil responses are not automatically interpreted as cognitive load, attention, arousal, stress, emotion, surprise, or effort; causal, adequacy, exclusion, and model-selection claims remain outside automated package decisions.

# gp3bayes 0.3.0.9000
### Public API and integration hardening

* Froze the 324-function development API in a machine-readable manifest
  and added tests for exported names and formal argument stability.
* Added source-level documentation coverage tests for all public exports.
* Added direct smoke tests for lightweight prediction, backend, LOO,
  prior-posterior, and Phase-4 table adapters.
* Added explicit malformed-input and combinatoric-boundary tests for
  fit-dependent extraction and prediction-comparison helpers.
* Added a complete public API map and a quality/failure-contract article.

This hardening phase adds no public functions and does not broaden the
approved model-family scope.

### Hierarchical and posterior-predictive atlases

* Added raw group-effect draw extraction, posterior rank probabilities,
  and baseline random-intercept latent variance partitions.
* Added governed numeric prediction profiles, finite-difference predictive
  gradients, two-dimensional prediction surfaces, and contrast profiles.
* Added posterior-predictive distribution and quantile atlases, posterior
  uncertainty in prediction scores, and binary calibration uncertainty.
* Added group-aggregated PSIS-LOO influence summaries and graphics.
* Added four articles covering the new hierarchical and predictive layer.

All additions remain descriptive under the fitted model. They do not add
causal derivatives, automatic ranking, automatic calibration certification,
automatic adequacy decisions, or automatic group exclusion.

### Evidence atlases, recovery graphics, and publication registries

* Added publication-oriented recovery, prior-sensitivity, estimand-
  sensitivity, group-deletion, random-slope, power-scale, and SBC adapters.
* Added a declared-prior versus posterior bridge with marginal shift,
  contraction, overlap, and empirical distance summaries.
* Added pointwise PSIS-LOO influence atlases without automatic exclusion.
* Added publication registries, evidence inventories, and non-interactive
  diagnostic dashboards with explicit file-output semantics.
* Added seven evidence/publication articles including an end-to-end showcase.

No addition performs automatic model selection, automatic exclusion,
automatic adequacy or robustness certification, or causal interpretation.

### Advanced predictive diagnostics and evidence graphics

* Added ROC, precision-recall, confusion, calibration-error, grouped
  calibration, predictive Q-Q, duration-tail, interval-width, posterior
  ranking, and posterior predictive discrepancy summaries.
* Added ggplot adapters for sensitivity suites, model-evidence inventories,
  backend parity/environment checks, analysis-manifest comparisons, schema
  comparisons, design-support audits, and missingness audits.
* Added structured model cards and reporting-evidence inventories with
  explicit Markdown output.
* Added four advanced post-fit articles and additional test coverage.

These additions are presentation and diagnostic layers. They do not add
automatic model selection, automatic adequacy certification, automatic
exclusion, or causal interpretation.


## Post-fit exploration, prediction, and publication layer

* Added standardized posterior-draw, sampler-diagnostic, log-likelihood,
  expected-prediction, posterior-predictive, and linear-predictor extraction.
* Added governed prediction grids and explicit prediction-support auditing.
* Added binary calibration, threshold metrics, predictive scores, duration
  quantile calibration, PIT summaries, predictive coverage, residual review,
  grouped posterior predictive checks, and descriptive uncertainty
  decomposition.
* Added group-effect, variance-component, LOO diagnostic, LOO comparison,
  and predictive-weight tables.
* Added a publication-oriented ggplot/bayesplot layer covering posterior
  intervals, densities, MCMC diagnostics, calibration, prediction intervals,
  hierarchical effects, uncertainty, and LOO influence/comparison.
* Added explicit figure sets and structured analysis bundles; no output is
  written without an explicit destination.
* Added five articles documenting posterior exploration, prediction and
  scoring, hierarchical uncertainty, LOO comparison, and publication bundles.

All additions remain within the approved hierarchical Bernoulli-logit and
positive uncensored lognormal-duration model families. They do not add
automatic model selection, automatic exclusions, adequacy claims, or causal
interpretation.

# gp3bayes 0.2.0

## 0.2.0 stabilization program

* Adds a stable family-neutral workflow API while retaining the existing
  binary- and duration-specific interfaces.
* Adds analysis manifests, data/specification fingerprints, explicit
  manifest freezing/comparison, and reproducibility reports.
* Adds pre-fit missingness, fixed-effect design, random-effect support,
  and combined design-support audits without automatic data/model changes.
* Adds declarative unified sensitivity suites and evidence inventories
  without aggregate robustness, adequacy, exclusion, or selection claims.
* Adds backend environment validation, MCSE-aware rstan/cmdstanr posterior
  parity auditing, and serialized gp3bayes object-schema contracts.
* Forward-ports CRAN 0.1.1 compliance safeguards: two-core automatic
  defaults, explicit report paths, temporary vignette outputs, and safe
  seed handling without direct global-environment modification.
* Adds five focused stabilization articles plus an integrated synthetic
  0.2.0 release case study, tests, and release smoke/audit scripts.


* Aligned DESCRIPTION, README, citation metadata, package-level help,
  backend-installation guidance, CRAN comments, and pkgdown deployment metadata
  with the complete 0.2.0 API and dual `rstan`/`cmdstanr`
  backend support.

## Specification closure

* Adds strict readiness checks for overall condition imbalance, binary group outcome variation, identifier-like numeric predictors, fixed-effect rank, duration extremes, declared duration ranges, censoring signals, and optional separation screening.
* Adds reusable transformation recipes with forward replay, inversion, and exact replay validation for retained rows.
* Adds first-class design-standardised binary probability contrasts and duration median, ratio, and predictive-quantile estimands.
* Adds governed structural, group-deletion, contrast-coding, predictor-scaling, and duration-unit sensitivity workflows without automatic model selection or exclusion.
* Adds detailed family-specific posterior predictive checks and plotting helpers.
* Adds a governed exact K-fold adapter through `brms::kfold()` as an optional predictive-validation fallback/complement to PSIS-LOO.
* Adds an auditable specification-traceability matrix, examples, smoke tests, and three integrated articles.

* Added optional power-scaling sensitivity integration through `priorsense`.
* Added conservative PSIS-LOO diagnostics, influence inspection, model
  comparison, and stacking or pseudo-BMA weights through `loo`.
* Added fixed-effects separation screening through `detectseparation`.
* Added simulation-based calibration plans and plots through `SBC`.
* Added restricted full-MCMC backend selection between `rstan` and
  `cmdstanr`.
* Added coefficient-specific interaction-prior defaults for binary and
  duration contracts.
* Added dedicated binary and duration pathology generators, evaluations,
  plots, tests, examples, smoke tests, and three integrated articles.

# gp3bayes 0.1.1

* Published `gp3bayes` 0.1.1 on CRAN after addressing CRAN review feedback.
* Added Zenodo DOI documentation and current release-status wording.
* Added explicit copyright-holder metadata for the initial CRAN submission.

# gp3bayes 0.1.0

* Created the independent `gp3bayes` package scaffold.
* Defined the initial scope as contract-first Bayesian workflows for
  hierarchical behavioural data.
* Restricted initial development to hierarchical Bernoulli-logit and
  hierarchical lognormal-duration model families.
* Added package-level documentation and explicit interpretation boundaries.
* Added the initial deterministic scope test using testthat edition 3.
* Added the MIT licence.
* Added standard GitHub Actions workflows for cross-platform R CMD check
  and pkgdown deployment.
* Added canonical repository, issue-tracker, and pkgdown website metadata.
* Added `create_model_contract()` for the two approved initial model
  families with neutral column mappings and explicit methodological
  specifications.
* Added a concise `gp3bayes_model_contract` print method and deterministic
  validation tests.
* Added `audit_model_readiness()` for backend-independent assessment of
  outcome validity, declared columns, missingness, repeated measurements,
  item and trial structure, predictors, interactions, time terms, and
  requested participant-level random slopes.
* Added structured `gp3bayes_readiness_audit` results with explicit pass,
  warning, and failure statuses and a concise print method.
* Added `build_model_formula()` for deterministic, backend-independent
  construction of approved fixed-effects, interaction, participant, item,
  time, and optional participant-level random-slope structures.
* Added `create_prior_specification()` and
  `validate_prior_specification()` for explicit binary-logit and
  lognormal-duration prior records without creating executable backend
  objects.
* Added `create_model_specification()` to combine a model contract,
  successful readiness audit, approved formula, and validated priors into
  one inspectable backend-independent specification.
* Added concise print methods and deterministic validation tests for
  formulas, priors, compatibility checks, and complete specifications.
* Added `simulate_hierarchical_binary_data()` for deterministic
  hierarchical Bernoulli-logit simulation with participant effects,
  optional crossed item effects, optional participant condition slopes,
  controlled imbalance, and a stored true-parameter record.
* Added `prepare_hierarchical_binary_data()` for explicit binary-outcome
  mapping, condition coding, recorded predictor scaling, missing-data
  decisions, readiness auditing, and fixed-effects matrix construction.
* Added `specify_binary_model()` to combine prepared data with the
  approved binary contract, restricted hierarchical formula, and
  validated backend-independent prior specification.
* Added `check_binary_prior_predictive()` for deterministic simulation
  of family-specific prior predictions and structured plausibility checks
  without fitting a model or requiring a Bayesian backend.
* Added concise print methods, generated documentation, and 89 focused
  tests for the backend-independent binary workflow foundation.
* Added repository and installed-package citation metadata through
  `CITATION.cff` and `inst/CITATION`.
* Refined the package description to match the currently implemented
  backend-independent contract, readiness, simulation, preparation,
  specification, and prior-predictive functionality.
* Added restricted binary model translation from approved package
  specifications to `brms` Bernoulli-logit formulas and priors.
* Added optional full-MCMC fitting through the fixed `brms` and `rstan`
  sampling route without unrestricted formulas or backend arguments.
* Added conservative fit metadata that records sampling settings while
  explicitly withholding convergence and posterior-adequacy claims.
* Added conservative binary posterior diagnostics covering R-hat,
  bulk and tail ESS, divergences, maximum-treedepth saturation, and
  chain-level energy diagnostics.
* Added posterior summaries, binary posterior predictive checks,
  prior-scale sensitivity, simulation-based recovery, diagnostic plots,
  and structured Markdown model reports.
* Diagnostic, predictive, sensitivity, and recovery statuses never create
  automatic convergence, adequacy, robustness, or validation claims.
* Added the complete hierarchical lognormal duration workflow for
  strictly positive finite uncensored outcomes.
* Added deterministic duration simulation, explicit unit conversion and
  preparation, model specification, prior predictive checks, restricted
  `brms` translation, and full MCMC fitting through `rstan`.
* Zero, negative, censored, truncated, shifted, survival, Gamma, Weibull,
  and mixture outcomes remain outside the approved duration contract.
* Added conservative duration posterior diagnostics, posterior summaries
  with median-ratio interpretation, posterior predictive checks,
  prior-scale sensitivity, simulation-based recovery, and structured
  Markdown reports.
* Duration validation statuses remain separate from automatic convergence,
  adequacy, robustness, causal, or substantive claims.
* Added integrated end-to-end binary and duration vignettes.
* Added dedicated articles for sampling diagnostics, prior sensitivity and
  recovery, and optional backend installation.
* Added a repository-only audit covering exports, Rd aliases, pkgdown
  reference topics, articles, built pages, and optional dependencies.
* Aligned DESCRIPTION, citation metadata, README, package documentation, and
  the curated pkgdown reference and article indices with the complete scope.
