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EconHDFE v0.7.0

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@github-actions github-actions released this 30 Sep 03:51
v0.7.0
a0305c3
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EconHDFE v0.7.0 — Alpha research release

中文

本次发布整合 Post/Prediction、IV 正确性修复以及中英文文档。项目仍为 Alpha 阶段研究软件。

  • 标准 OLS/线性 IV 支持冻结设计状态、分块 predict()、原始样本行位置恢复，以及显式 save_fe=True 保存的分类固定效应预测。未知类别、违反嵌套关系和未识别组合明确拒绝。
  • 线性组合与 Wald 检验保留非有限值、负方差、秩亏和零方差保护；stdp 仅包含 beta 协方差，不包含固定效应不确定性或完整预测区间。
  • IV 增加矩条件识别与数值秩保护；敏感 2SLS 使用压缩工具变量空间 QR/SVD；修正加权 first-stage fitted 值的坐标及 fixed-k 协方差，并使用调用内有界诊断缓存。
  • 整合此前 0.6.4/0.6.5 开发线的资源边界守卫与测试体系整理。测试入口为 python scripts/run_tests.py --suite full；普通 pytest 只运行日常核心集。
  • 中英文首页、技术文档、历史目录和发布打包入口统一。旧持久化结果缓存按 ABI 安全失效；已有 within 数值缓存 ABI 不变。

支持 Python 3.10–3.13。升级命令：pip install --upgrade econhdfe==0.7.0。

发布流程使用成功的 16 环境 CI（Linux/macOS/Windows 与可行最低依赖环境）及 bundle 验证产出的冻结制品，经独立验收后发布；GitHub Release 与 PyPI wheel/sdist 字节相同，哈希见 SHA256SUMS.txt。

边界：不包含 PPML/IV-PPML、varying-slope/group+individual FE 样本外预测、margins/AME；不新增 licensed-Stata/upstream 外部认证、普遍提速或全流程内存预算保证。Lean 证明覆盖明确假设下的数学命题，不等于 Python/Numba 浮点程序的形式验证或历史原创性认证。

English

This alpha research release brings together Post/Prediction, IV correctness fixes, and bilingual documentation.

  • Standard OLS and linear IV gain frozen prediction state, chunked prediction, original-row restoration, and explicitly saved categorical fixed effects. Unknown categories and unidentified or inconsistent FE combinations fail explicitly.
  • Linear contrasts and Wald tests retain finite-value, variance and rank safeguards. Prediction stdp is beta-only; it is not a full prediction interval or an estimate of FE uncertainty.
  • IV estimation adds cross-moment identification/rank guards and a compressed instrument-coordinate QR/SVD solve for sensitive 2SLS systems. Weighted first-stage coordinates and fixed-k covariance are corrected, with bounded call-local diagnostic reuse.
  • Includes resource guards and the reorganized full test suite from the unreleased 0.6.4/0.6.5 development lines, together with English/Chinese documentation and packaging cleanup.

Python 3.10–3.13 is supported. Install with pip install --upgrade econhdfe==0.7.0.

Publication consumes the frozen candidate from successful matrix and bundle validation after detached acceptance; it does not rebuild after tagging. GitHub and PyPI share the exact wheel/sdist bytes.

PPML/IV-PPML prediction, varying-slope/group+individual FE prediction, margins/AME, complete FE uncertainty and full external Stata/upstream certification remain outside this release's claims. No universal performance, end-to-end memory-bound or implementation-formal-verification claim is added.

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EconHDFE v0.6.3 — Alpha Research Release

EconHDFE v0.6.3 — Alpha Research Release

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@github-actions github-actions released this 26 Sep 19:42
v0.6.3
2782d93

EconHDFE v0.6.3 — Alpha Research Release

v0.6.3 is the first release candidate to complete the package's full cross-platform release gate.

Highlights

  • Keeps the shared OLS / linear-IV / PPML / IV-PPML HDFE architecture and public estimator contracts unchanged.
  • Fixes Python 3.10/3.11 compatibility-gate reflection differences.
  • Fixes Windows newline-sensitive release checks.
  • Hardens managed Numba workqueue concurrency and bootstrap BLAS thread control.
  • Uses an isolated sdist-to-wheel build path and verifies clean installations.
  • Separates original and public-redacted benchmark provenance without weakening hash checks.

Validation

  • Linux / Windows / macOS × Python 3.10–3.13: 12/12 environments passed.
  • Four feasible minimum-runtime-dependency environments passed.
  • Each CI environment: 928 passed, 1 skipped, 0 failed.
  • Local full suite with the optional exact backend: 929 passed.
  • Frozen wheel numerical recheck: 350 passed.
  • Final bundle verification and detached formal release gate passed.

The single CI skip is an optional exact-backend test; it was executed successfully in the local full suite.

Release identity

This release is built from and tagged at commit:

2782d93f901ec1eed28ac0f963834701e0a44b09

The uploaded artifacts are the already-validated frozen artifacts; they are not rebuilt after tagging.

Status and external validation boundary

EconHDFE remains an alpha research release. Licensed-Stata/upstream external certification remains a separate boundary. This release does not add a universal performance claim or an independent mathematical-novelty certification.

See SHA256SUMS.txt in the release assets for exact artifact hashes.

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