American Psychological Association 6th edition

Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda, & Shohei Shimizu. (2023). Python package for causal discovery based on Li NGAM. Journal of Machine Learning Research, 24, 1-8.

ISO-690 (author-date, English)

TAKASHI IKEUCHI, MAYUMI IDE, YAN ZENG, TAKASHI NICHOLAS MAEDA und SHOHEI SHIMIZU, 2023. Python package for causal discovery based on Li NGAM. Journal of Machine Learning Research. 1 Januar 2023. Vol. 24, , p. 1-8.

Modern Language Association 9th edition

Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda, und Shohei Shimizu. „Python Package for Causal Discovery Based on Li NGAM.“. Journal of Machine Learning Research, Bd. 24, Januar 2023, S. 1-8.

Mohr Siebeck - Recht (Deutsch - Österreich)

Takashi Ikeuchi/Mayumi Ide/Yan Zeng/Takashi Nicholas Maeda/Shohei Shimizu: Python package for causal discovery based on Li NGAM., Journal of Machine Learning Research 2023, 1-8.

Emerald - Harvard

Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda und Shohei Shimizu. (2023), „Python package for causal discovery based on Li NGAM.“, Journal of Machine Learning Research, Vol. 24, S. 1-8.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.