kpcalg
1.0.1Kernel PC Algorithm for Causal Structure Detection
Overview
Kernel PC (kPC) algorithm for causal structure learning and causal inference using graphical models. kPC is a version of PC algorithm that uses kernel based independence criteria in order to be able to deal with non-linear relationships and non-Gaussian noise.
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Documentation
- Examples that run
- 78%
- Documented parameters
- 96%
- Return-value docs
- 100%
- References docs
- 67%
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Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.5.0 released · 2025-04-11
- archivedRemoved from CRAN2025-03-24email to the maintainer is undeliverable
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 1.0.12017-01-22
- RR 3.3.0 released · 2016-05-03
Package metadata
- Total releases
- 1
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.0.2
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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