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Capability

DoubleML Python tool

Estimate and infer target parameters in specified causal models using double/debiased machine learning; identification assumptions remain the researcher's responsibility.

Community indexedEconomics and business

Capability details

What this helps you do

Estimate and infer target parameters in specified causal models using double/debiased machine learning; identification assumptions remain the researcher's responsibility.

Catalog editorial description

View description sources

editor · 2026-09-18 — Catalog classification and summary; not maintainer acknowledgement.

Research classification

Economics and business

View discipline evidence

editor · 2026-09-18 — 依据原始用途对项目与核心工具提出FORD 5.2分类;属于科研任务子集,不替代开放科研网络整体定位。

Who it is for

An intended audience has not been supplied. Check the original documentation for suitability and prerequisites.

How to use it

Follow upstream guidance and source conditions.

AIPOCH has not verified execution.

Read usage documentation

Inputs

  • 结果Y、处理D、协变量X、可选工具变量及学习器/重采样设置。

Outputs

  • 目标参数、标准误、置信区间等推断量。

Resource type

Tool

Execution guidance

community described

Read execution guidance

Access conditions

  • 固定LICENSE为BSD3条款。
  • 依赖scikit-learn等Python生态;机器学习不能自动证明因果识别,R twin属于另一实现。
  • Community indexing of this software or analysis workflow only. External models, datasets, services and third-party components have separate terms. Installation, scientific accuracy and suitability were not validated.
View usage information sources

Inputs

editor · 2026-09-18 — Catalog classification and summary; not maintainer acknowledgement.

Outputs

editor · 2026-09-18 — Catalog classification and summary; not maintainer acknowledgement.

Access conditions

editor · 2026-09-18 — Catalog classification and summary; not maintainer acknowledgement.

Documentation

editor · 2026-09-18 — Catalog classification and summary; not maintainer acknowledgement.

Sources & versions

DoubleML/doubleml-for-py
Reference role
implementation
Last successful public check
2026-09-22T08:38:02.404Z
Latest public check attempt
2026-09-22T08:38:02.404Z · ok
GitHub metrics
Stars 788 · checked · latest attempt 2026-09-22T08:38:02.404Z (ok)
Forks 128 · checked · latest attempt 2026-09-22T08:38:02.404Z (ok)
Latest default-branch commit

4e51b3ebb8784fb77c3902b0d3c504b46e53149f
Observed 2026-09-22T08:38:02.404Z
Source activity check
fresh · last successful check 2026-09-22T08:38:02.404Z · latest attempt 2026-09-22T08:38:02.404Z (ok)
Source status
Active at last observation
License
BSD-3-Clause
Fixed commit
1808b07a13cc8c61f508c1ed6aec658ea32a2807
Reference checked
2026-09-18
Download source at this commit

Default-branch activity is separate from the fixed reference above. Source terms apply. A fixed commit identifies content; it does not establish scientific validity.

Related research

DoubleML PythonCommunity indexed

Estimate and infer target parameters in specified causal models using double/debiased machine learning; identification assumptions remain the researcher's responsibility.

Research discipline Economics and businessReusable outputs 1
Economics and businessDoubleML/doubleml-for-py
Added Change observed by
GitHub · DoubleML/doubleml-for-pyStars 788Forks 128

Claims & evidence

No maintainer acknowledgement or scientific validation is recorded for this entry. Community indexing only describes its inclusion in this catalog.

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Research questions and code contributions belong with the original project. Catalog corrections can be proposed separately.

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