ZengZichao/dsh-revbayes-forge--packages-pack-model-selection ↗★ 0

dsh-revbayes-forge-pack-model-selection

Development fixture package for the model-selection model pack bundled inside dsh-revbayes-forge. 适合需要构建边际似然脚本并使用步石或路径采样估算器的开发者。

패키지
dsh-revbayes-forge-pack-model-selection
호환성
미검증
버전
0.1.0
라이선스
GPL-3.0
최근 업데이트
2026. 10. 23.

설치

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Model Selection pack

Development fixture package dsh-revbayes-forge-pack-model-selection of the RevBayes Forge plugin (dsh-revbayes-forge).

English

  • Pack id: model-selection
  • Tool: revbayes_model_selection
  • Maturity: golden

What it generates. Builds marginal-likelihood scripts that wrap a base script or base spec in a power posterior and attach a stepping-stone (steppingStoneSampler) or path-sampling (pathSampler) estimator. Steps (cats >= 2), burn-in, and sampling frequency are validated; the resulting runs are computationally expensive.

Analyses.

AnalysisTitleCanonical golden
stepping_stoneStepping-stonestepping_stone.Rev
path_samplingPath samplingpath_sampling.Rev
marginal_likelihoodMarginal likelihood—

Full spec fields, data requirements, and limitations: docs/en/model-packs.md.

Fixtures. Files under fixtures/ are synthetic small datasets shipped with the repository; they back the golden scripts, canonical specs, and runtime checks used by npm test and npm run test:runtime.

Enablement. Enable this pack in the settings page (RevBayes Forge → Packs); no separate installation is needed.


中文

  • Pack id:model-selection
  • 工具:revbayes_model_selection
  • 成熟度:golden

生成内容。 生成边际似然脚本:把 base 脚本或 base spec 包进 power posterior,并附加 stepping-stone(steppingStoneSampler)或 path-sampling(pathSampler)估计器。校验步数(cats >= 2)、burn-in 与采样频率;生成的计算开销较大。

分析列表。

AnalysisTitleCanonical golden
stepping_stoneStepping-stonestepping_stone.Rev
path_samplingPath samplingpath_sampling.Rev
marginal_likelihoodMarginal likelihood—

完整 spec 字段、数据要求与限制:docs/zh/model-packs.md。

夹具数据。 fixtures/ 下的文件均为随仓库分发的合成小数据,支撑 golden 脚本、canonical spec 与运行时检查,供 npm test 与 npm run test:runtime 使用。

启用方式。 在设置页(RevBayes Forge → Packs)勾选启用即可,无需单独安装。