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Changelog

Unreleased

Design & CLI

  • CLI: added --dry-run flag to lrdbench run to preview the record-estimator grid without fitting estimators or writing outputs.
  • Core: added BenchmarkRunner.preview() method for dry-run record materialisation and grid-size reporting.
  • Contracts: added machine-readable manifest JSON Schema at configs/contracts/manifest_schema.json.

Documentation & Onboarding

  • Docs: promoted dry-run workflow guidance into README, quickstart, benchmark protocol, and contributor smoke-test instructions.
  • Docs: expanded API reference coverage for BenchmarkRunner.preview(), schema dataclasses, validation/output-contract helpers, bootstrap utilities, plugin discovery, public assets, and testing helpers.
  • Packaging/docs: clarified that the all optional extra includes data-driven dependencies and documented lighter development-install alternatives.
  • Docs: rewrote docs/architecture.md into a full contributor guide covering the benchmark loop, module responsibilities, extension points, provenance, and output contract.
  • Docs: expanded CONTRIBUTING.md with architecture pointers, validation commands, and smoke-test verification steps.
  • Docs: added docs/faq.md covering installation errors, manifest validation, estimator invalidity, bootstrap intervals, reproducibility checks, caching, plugins, and observational CSV workflows.
  • Docs: added docs/parameter_glossary.md with tables explaining common parameters across all estimator families and execution blocks.
  • Docs: added bootstrap methodology section to docs/benchmark_protocol.md documenting the default block-length choice and override mechanism.
  • Notebooks: fleshed out all four tutorial notebooks with explanatory markdown, intermediate printouts, and additional code cells (estimates-vs-truth plots, failure-map inspection, stability metrics, and custom-estimator walkthroughs).
  • Terminology: aligned all canonical suite manifests to use family: temporal consistently (previously time_domain in YAMLs vs temporal in docs).

API Documentation

  • Core: added comprehensive docstrings to BaseEstimator, BaseGenerator, BaseContamination, BaseEvaluator, BaseReporter, BaseResultStore, BenchmarkRunner.run(), run_manifest_path(), run_manifest_mapping(), and key schema dataclasses (SeriesRecord, EstimateResult, EstimatorSpec, MetricSpec, TruthSpec).
  • Core: expanded docstrings for bootstrap_statistic_distribution, symmetric_percentile_cis, and circular_block_resample.

Mathematical Implementation Hardening

  • Estimators: deduplicated GPH and Periodogram regression cores into a shared _log_periodogram_regression_d() with optional taper support.
  • Estimators: fixed GPH to honour the manifest m bandwidth parameter when using the shared regression core.
  • Estimators: added cosine-bell (taper: cosine) spectral tapering to GPH and Periodogram to reduce periodogram bias from spectral leakage.
  • Estimators: added Anis-Lloyd finite-sample correction to RS as an opt-in parameter use_anis_lloyd_correction. Uses the exact 1976 formula computed via scipy.special.gammaln for numerical stability.
  • Estimators: corrected RS estimation to fit the R/S log-log slope across subseries scales rather than deriving the Hurst proxy from a single full-record R/S value.
  • Estimators: documented the GHE flat_slope_tol heuristic explicitly in docstrings and docs/estimator_status.md. Users can disable it by setting flat_slope_tol: 0.0.
  • Estimators: documented the known finite-sample bias of the classical RS estimator in docs/estimator_status.md.
  • Generators: updated simulate_fou docstring to state clearly that it uses a first-order Euler–Maruyama-style discretisation and is not an exact simulation of the continuous fOU process.

Plugin discovery (prior)

  • Plugin discovery: added automatic third-party estimator loading via LRD_BENCH_ESTIMATOR_PLUGIN (import-style) and LRD_BENCH_ESTIMATOR_PLUGIN_PATH (file-path) environment variables.
  • CLI: added --no-plugins flag to lrdbench run and lrdbench list-estimators to skip automatic plugin discovery.
  • CLI: added lrdbench list-plugins command to inspect discovered third-party plugins.
  • Core: added lrdbench.plugin_loader module with safe, failure-transparent plugin loading.
  • Core: BenchmarkRunOutput now carries plugin_provenance to track loaded plugins, versions, source hashes, and load failures.
  • Docs: updated estimator contract and third-party estimator workflow for plugin discovery.
  • Estimators: added aggregation-based temporal Hurst-proxy estimators AbsoluteMoment, Variance, and VarianceResidual.
  • Docs: added bundled-estimator documentation covering registry names, targets, parameters, and aggregation-method interpretation notes.
  • Estimators: added experimental data-driven baselines MLRandomForest, MLSVR, MLCNN, and MLLSTM targeting hurst_scaling_proxy.
  • Manifests: added optional ml_training for run-local supervised training before benchmark estimation.
  • Suites/examples: added smoke_data_driven.yaml and examples/data_driven_baseline_benchmark.py for RF/SVR stress-test comparison.
  • Docs: added data-driven estimator installation, manifest, interpretation, and artefact guidance.

1.0.2

  • Packaging: first PyPI-published stable package release.
  • Public contract: unchanged at 1.0.0; no schema, metric, manifest, or output-column changes.

1.0.1

  • Packaging: internal packaging-only release candidate for PyPI publication.

  • Public contract: unchanged at 1.0.0; no schema, metric, manifest, or output-column changes.

  • CI: updated GitHub-hosted workflow actions to Node 24-compatible major versions.

  • Release: configured the tag release workflow to publish built distributions to PyPI through Trusted Publishing using the pypi GitHub environment.
  • Docs: updated Read the Docs references now that the hosted documentation project exists.

1.0.0

  • Release: promoted the public research framework from v0.9.0-rc1 to stable v1.0.0.
  • Public contract: advanced the output contract to 1.0.0 without changing required files or required columns from the release candidate.

  • Docs: added governance and maintenance policy, clarified DOI-free citation status, and updated migration notes for the stable public release.

  • Release candidate: advanced package metadata to 0.9.0rc1 and public output contract to 0.9.0-rc1 for schema-freeze review.

  • Docs: added release-candidate freeze notes, migration notes, and citation guidance for independent public use.
  • Release: replaced placeholder release workflow with a build/check/upload-artifact workflow for tagged release-candidate artefacts.
  • Docs: started external contributor beta with estimator onboarding guide, expanded estimator contract, contributor checklist, and issue templates.
  • Docs: added third-party estimator workflow and leaderboard submission policy.
  • Examples: added a minimal custom estimator, a programmatic custom-estimator benchmark, and test utilities for estimator-author smoke tests.
  • CLI: added lrdbench list-metrics and lrdbench list-estimators discovery commands.
  • CLI: added lrdbench list-suites and public suite-name resolution for run and validate.
  • CLI: added lrdbench validate-output <run_root> to check generated reports against the public output contract.
  • Public contract: added machine-readable output contract for required report/result-store files and columns.
  • Docs: added output-contract and reproducibility guides for public benchmark beta users.
  • Docs: added public-medium reference output counts for contract-valid local runs.
  • Packaging: added CI packaging workflow and verified local sdist/wheel build plus installed console-script and smoke-report contract checks.
  • Packaging: included tracked public suite manifests and output contract assets in built wheels.
  • Validation: added statistical generator checks for fGn/fBm scaling, ARFIMA memory behavior, MRW intermittency, and fOU mean reversion.
  • Validation: added statistical estimator checks for baseline Hurst-proxy and spectral long-memory estimators on known fGn/ARFIMA regimes.
  • Test coverage: added behavior checks for contamination operators and broader wavelet estimator validity/failure paths.
  • Test coverage: added observational-source loader checks for inline and CSV-backed series.
  • Docs: added public failure-mode taxonomy and known-limitations pages, and expanded estimator status metadata with assumptions, expected regimes, and failure risks.
  • CLI: added lrdbench validate <manifest> for manifest-only checks without running benchmarks.
  • Public suites: added tracked public_small_* benchmark manifests for canonical ground-truth, stress contamination, null false-positive, and sensitivity/disagreement public-alpha checks.
  • Public suites: added first-pass tracked public_medium_* manifests for more serious local benchmark campaigns.
  • Documentation: added tracked design specification and estimator status pages for public-alpha interpretation.
  • Documentation: added explicit interpretation semantics for aggregation, uncertainty, leaderboards, and failure outputs.
  • Documentation: recorded public-small expected output artefacts and local reference run counts.
  • Reporting: default plotting configuration now uses a writable local matplotlib cache when MPLCONFIGDIR is unset, avoiding read-only home-directory warnings in sandboxed runs.
  • Leaderboards: balanced-global diagnostic rows whose names are not declared estimator specs (for example __all_estimators__) are no longer ranked as estimators.
  • Documentation/handoff: added tracked clean-clone paper workflow documentation, fixed the MkDocs nav entry for strict builds, and clarified that the frozen design PDF is local-only unless explicitly restored.
  • Paper workflow (local only): publication-oriented benchmark manifests, optional python -m paper_support.run_paper_suites, staged LaTeX/figures, and run_index.csv are not tracked on the remote repository—see .gitignore and docs/development_handoff.md. Core reporting (LaTeX, figures, metrics) remains in the library for any manifest you run.
  • Report polish/completeness: estimator metadata, failures, environment snapshot, artefact index, raw artefact metadata exports, richer HTML sections, and publication-oriented LaTeX tables for disagreement, sensitivity, benchmark uncertainty, and failures.
  • Report figures: core matplotlib/seaborn plotting support for opt-in disagreement/sensitivity heatmaps, benchmark uncertainty interval plots, and false-positive LRD plots.
  • Benchmark-level uncertainty: optional manifest uncertainty block, aggregate bootstrap CIs, paired bootstrap estimator differences, raw uncertainty metric scope, and benchmark_uncertainty.csv.
  • Scale/window sensitivity: estimator manifest variants, parameter_variant_sensitivity, max_variant_drift, and scale_window_sensitivity.csv.
  • Estimator disagreement metrics: added cross-estimator dispersion, pairwise estimator disagreement, family-level disagreement summaries, and estimator_disagreement.csv.
  • Stress-test reporting: contamination severity metadata, failure_map.csv, and false_positive_lrd_rate with manifest-configurable threshold/null handling.
  • Synthetic generators: added MRW and fOU generator support.
  • Phase 6 documentation: MkDocs + Material (mkdocs.yml), Read the Docs config (.readthedocs.yaml), expanded docs/ pages, pymdownx snippets for root markdown, GitHub Action docs.yml for mkdocs build --strict, and Documentation URL in pyproject.toml.
  • Phase 5 execution: optional execution.max_workers for threaded parallel fits, optional execution.estimate_cache_dir (+ cache_read / cache_write) for on-disk pickled EstimateResult reuse; manifest validation for execution keys.
  • Repository layout: benchmark YAML suites under configs/suites/; scaffold configs/{estimators,generators,contaminations,reports}/, docs/, examples/, and tests/{unit,integration,…} per lrdbench_repo_schema.txt. Optional local-only paper_support/ and configs/suites/paper/ (ignored by Git) may mirror that layout for drafts.

0.1.0

  • Initial public alpha: ground-truth, stress-test, and observational modes; baseline estimators and generators; CSV/HTML reporting.