docs(readme): surface v1.4.2 release notes in README + README_CN

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: brycewang-stanford

README.md

@@ -15,7 +15,18 @@ StatsPAI is the **agent-native** Python package for causal inference and applied
 
 It brings R's [Causal Inference Task View](https://cran.r-project.org/web/views/CausalInference.html) (fixest, did, rdrobust, gsynth, DoubleML, MatchIt, CausalImpact, ...) and Stata's core econometrics commands into a single, consistent Python API.
 
-**🎉 NEW in v1.4.1 — v3-frontier Sprint 3: AKM shock-clustered SE, Claude extended thinking, parity + integration suites, 2 new guides**
+**🎉 NEW in v1.4.2 — correctness patches + Proximal / QTE / Causal-RL family guides**
+
+StatsPAI 1.4.2 is a patch release.  No breaking changes, no new public signatures — just two silent-wrong-numbers fixes and three family guides closing the last gaps between the v3 reference and the published documentation.
+
+- **⚠️ correctness fix — `sp.dml_model_averaging` √n SE scaling bug.** The cross-candidate variance aggregator treated the sample-mean influence-function outer product as `Var(θ̂_avg)` directly, missing a final `/ n`. Reported SEs were `√n` times too large; on the canonical n=400 DGP the 95% CI width was 4.20 (nominal ≈ 0.21) and empirical coverage was 100%. After the fix, CI width is 0.21 and coverage is ≈ nominal. Regression guard: `tests/test_dml_model_averaging.py::test_se_on_correct_scale`.
+- **⚠️ correctness fix — `sp.gardner_did` event-study reference-category contamination.** Stage-2 dummy regression pooled never-treated units *and* treated units outside the event-study horizon into a single baseline, dragging every event-time coefficient toward the mean of that pool. On a synthetic panel with true τ=2 and strict parallel trends, pre-trends came out ≈ -0.30 (should be 0) and post ≈ +1.72 (should be 2.0). Replaced the Stage-2 regression in event-study mode with direct Borusyak-Jaravel-Spiess-style within-(cohort × relative-time) averaging of the imputed gap. After the fix: pre-trends ≈ +0.01, post ≈ +2.02. Non-event-study single-ATT path was already correct and is unchanged.
+- **New family guides** — `docs/guides/proximal_family.md` (full Proximal Causal Inference walkthrough covering `sp.proximal`, `sp.fortified_pci`, `sp.bidirectional_pci`, `sp.pci_mtp`, `sp.double_negative_control`, `sp.proximal_surrogate_index`, `sp.select_pci_proxies` with a decision tree + 4 diagnostics every PCI analysis should report), `docs/guides/qte_family.md` (mean → quantile → distribution with cross-section / DiD / IV / panel decision paths across `sp.qte`, `sp.qdid`, `sp.cic`, `sp.distributional_te`, `sp.dist_iv`, `sp.kan_dlate`, `sp.beyond_average_late`, `sp.qte_hd_panel`), `docs/guides/causal_rl_family.md` (when to use causal RL vs classical CI, covering `sp.causal_bandit`, `sp.causal_dqn`, `sp.offline_safe_policy`, `sp.counterfactual_policy_optimization`, `sp.structural_mdp`, `sp.causal_rl_benchmark` + 4 causal-RL-specific sanity checks).
+- **Formally shipped from v1.4.1 cherry-picks** — `tests/test_bridge_full.py` (10 end-to-end tests for `sp.bridge(kind=...)` bridging theorems) and `docs/guides/bridging_theorems.md`.
+
+Every public signature is byte-for-byte identical to v1.4.1.  Upgrading reveals narrower CIs for `dml_model_averaging` and cleaner event-study coefficients for `gardner_did`.
+
+**Previously in v1.4.1 — v3-frontier Sprint 3: AKM shock-clustered SE, Claude extended thinking, parity + integration suites, 2 new guides**
 
 StatsPAI 1.4.1 is an additive follow-up to 1.4.0 that closes the Sprint 3 items:
 
@@ -981,7 +992,7 @@ pytest
   author={Wang, Biaoyue},
   year={2026},
   url={https://github.com/brycewang-stanford/statspai},
-  version={1.4.1}
+  version={1.4.2}
 }
 ```
 

README_CN.md

@@ -15,7 +15,18 @@ StatsPAI 是一个**面向 AI Agent** 的 Python 因果推断与应用计量经
 
 它将 R 的 [Causal Inference Task View](https://cran.r-project.org/web/views/CausalInference.html)（fixest、did、rdrobust、gsynth、DoubleML、MatchIt、CausalImpact、sfaR、lme4、oaxaca、ddecompose……）和 Stata 的核心计量命令（`frontier`、`xtfrontier`、`mixed`、`meglm`、`mixlogit`、`ivqreg`……），统一到一个一致的 Python API 中。
 
-**🎉 v1.4.1 新版本 — v3 前沿 Sprint 3：AKM 冲击聚类 SE、Claude 扩展思考、对齐与集成测试套件、2 篇新指南**
+**🎉 v1.4.2 新版本 — 正确性补丁 + Proximal / QTE / 因果 RL 家族指南**
+
+StatsPAI 1.4.2 是 patch 版本。无破坏性改动、无新增公开签名——只修了两个"悄悄算错"的 bug，补上三篇家族指南，关闭 v3 参考文档和公开文档之间的最后几处缺口。
+
+- **⚠️ 正确性修复 — `sp.dml_model_averaging` 的 √n SE 尺度 bug**：候选间方差聚合器把"样本均值影响函数的外积"当成了 `Var(θ̂_avg)` 本身，漏掉了最后的 `/ n`。报告的 SE 因此比真值大 `√n` 倍；在典型 n=400 DGP 上，95% CI 宽度 4.20（理论 ≈ 0.21），实证覆盖率 100%（名义 95%）。修复后 CI 宽度 0.21，覆盖率回到名义水平。回归守卫加在 `tests/test_dml_model_averaging.py::test_se_on_correct_scale`。
+- **⚠️ 正确性修复 — `sp.gardner_did` event-study 参照组污染**：Stage-2 dummy 回归把"从未处理单元"和"处在 event-study 视野之外的已处理单元"合并成同一个基线，把每个 event-time 系数都往这个混合基线的均值拖。τ=2 且严格平行趋势的合成面板上，pre-trend ≈ -0.30（应为 0），post ≈ +1.72（应为 2.0）。Event-study 模式下改用 Borusyak-Jaravel-Spiess 风格的 (cohort × relative-time) 分箱直接聚合 imputed gap。修复后 pre-trend ≈ +0.01，post ≈ +2.02。非 event-study 的单 ATT 路径本来就对，保持不变。
+- **新增家族指南**：`docs/guides/proximal_family.md`（Proximal 因果推断家族完整走查，覆盖 `sp.proximal`、`sp.fortified_pci`、`sp.bidirectional_pci`、`sp.pci_mtp`、`sp.double_negative_control`、`sp.proximal_surrogate_index`、`sp.select_pci_proxies`，含决策树与 PCI 分析必报的 4 项诊断）；`docs/guides/qte_family.md`（均值 → 分位数 → 整分布三级粒度，配 cross-section / DiD / IV / 面板四条决策路径，覆盖 `sp.qte`、`sp.qdid`、`sp.cic`、`sp.distributional_te`、`sp.dist_iv`、`sp.kan_dlate`、`sp.beyond_average_late`、`sp.qte_hd_panel`）；`docs/guides/causal_rl_family.md`（何时用 causal RL 而非经典因果推断，覆盖 `sp.causal_bandit`、`sp.causal_dqn`、`sp.offline_safe_policy`、`sp.counterfactual_policy_optimization`、`sp.structural_mdp`、`sp.causal_rl_benchmark`，附 4 项 causal-RL 专属 sanity check）。
+- **v1.4.1 cherry-pick 的正式发版**：`tests/test_bridge_full.py`（`sp.bridge(kind=...)` 桥梁定理的 10 个端到端测试）与 `docs/guides/bridging_theorems.md`。
+
+所有公开签名与 v1.4.1 逐字节一致。升级后唯一可见的变化：`dml_model_averaging` 的 CI 会变窄、`gardner_did` 的 event-study 系数会更干净。
+
+**v1.4.1 — v3 前沿 Sprint 3：AKM 冲击聚类 SE、Claude 扩展思考、对齐与集成测试套件、2 篇新指南**
 
 StatsPAI 1.4.1 在 1.4.0 基础上做增量更新，关闭 Sprint 3 的 4 项工作：
 
@@ -375,7 +386,7 @@ pytest
   author={Wang, Biaoyue},
   year={2026},
   url={https://github.com/brycewang-stanford/statspai},
-  version={1.4.1}
+  version={1.4.2}
 }
 ```