From c05bf33c9def3e64aa32959baa359ca7e17d0cf9 Mon Sep 17 00:00:00 2001 From: Matt McKay Date: Mon, 5 Oct 2026 12:55:57 +1100 Subject: [PATCH 1/2] Update translation: lectures/bayes_nonconj.md --- lectures/bayes_nonconj.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/lectures/bayes_nonconj.md b/lectures/bayes_nonconj.md index 14d98360..376e6a37 100644 --- a/lectures/bayes_nonconj.md +++ b/lectures/bayes_nonconj.md @@ -4,7 +4,7 @@ jupytext: extension: .md format_name: myst format_version: 0.13 - jupytext_version: 1.16.4 + jupytext_version: 1.17.2 kernelspec: display_name: Python 3 (ipykernel) language: python @@ -354,7 +354,11 @@ NumPyro通过让`TruncatedNormal`经过`ExpTransform`来构造这个分布。 def truncated_lognormal(μ, σ): "截断到单位区间(0, 1]的对数正态分布。" base = dist.TruncatedNormal(loc=μ, scale=σ, low=-jnp.inf, high=0.0) - return dist.TransformedDistribution(base, dist.transforms.ExpTransform()) + # 声明(0, 1]这个支撑范围：单独使用ExpTransform会声明支撑为(0, ∞)， + # 这会让采样器提议出θ > 1的取值 + class _UnitLogNormal(dist.TransformedDistribution): + support = dist.constraints.interval(0.0, 1.0) + return _UnitLogNormal(base, dist.transforms.ExpTransform()) prior_ln = truncated_lognormal(0.0, 1.0) mcmc_ln = run_nuts(binomial_model, prior_ln, k, n) From 6f627a5f92a5bdd432a5ff8a8866457054cf5377 Mon Sep 17 00:00:00 2001 From: Matt McKay Date: Mon, 5 Oct 2026 12:55:58 +1100 Subject: [PATCH 2/2] Update translation: .translate/state/bayes_nonconj.md.yml --- .translate/state/bayes_nonconj.md.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.translate/state/bayes_nonconj.md.yml b/.translate/state/bayes_nonconj.md.yml index edbd635c..30ca6d5a 100644 --- a/.translate/state/bayes_nonconj.md.yml +++ b/.translate/state/bayes_nonconj.md.yml @@ -1,6 +1,6 @@ -source-sha: b78fbcddae98a645bff0f01bb28a1e7955db5f53 -synced-at: "2026-07-18" +source-sha: d9caa8174ac100d375f2a0742b47fe6326b229ac +synced-at: "2026-10-05" model: claude-sonnet-5 -mode: RESYNC +mode: UPDATE section-count: 6 -tool-version: 0.17.0 +tool-version: 0.29.3