Articles liés à Graphical Models and Causal Discovery with R: 100 Exercises...
Synopsis
Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical inference, and graph theory, the book offers a systematic pathway from foundational principles to cutting-edge algorithms, including independence tests, the PC algorithm, LiNGAM, information criteria, and Bayesian methods. Far more than a theoretical treatment, this volume emphasizes hands-on learning through R implementations, carefully designed exercises with solutions, and intuitive graphical illustrations. Readers will gain the ability to see, run, and understand causal discovery methods in practice.
Key features of this book include:
- A clear and self-contained introduction, bridging probability, statistics, and modern causal discovery techniques
- 100 exercises with solutions, supporting self-study and classroom use
- Reproducible R code, allowing readers to implement and extend the methods themselves
- Intuitive figures and visual explanations that clarify abstract concepts
- Broad coverage of applications within statistics and data science, connecting rigorous theory with modern machine learning and causal inference
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Joe Suzuki is a professor of statistics at Osaka University, Japan
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Graphical Models and Causal Discovery with R: 100 Exercises for Building Logic
Edité par
Springer, 2026
ISBN 10 : 9819542669
ISBN 13 : 9789819542666
Ancien ou d'occasion
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Vendeur : Big River Books, Powder Springs, GA, Etats-Unis
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Etat : good. This book is in good condition. The cover has minor creases or bends. The binding is tight and pages are intact. Some pages may have writing or highlighting. N° de réf. du vendeur BRV.9819542669.G
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Graphical Models and Causal Discovery with R
Edité par
Springer Verlag, Singapore Mai 2026, 2026
ISBN 10 : 9819542669
ISBN 13 : 9789819542666
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical inference, and graph theory, the book offers a systematic pathway from foundational principles to cutting-edge algorithms, including independence tests, the PC algorithm, LiNGAM, information criteria, and Bayesian methods. Far more than a theoretical treatment, this volume emphasizes hands-on learning through R implementations, carefully designed exercises with solutions, and intuitive graphical illustrations. Readers will gain the ability to see, run, and understand causal discovery methods in practice.Key features of this book include:A clear and self-contained introduction, bridging probability, statistics, and modern causal discovery techniques100 exercises with solutions, supporting self-study and classroom useReproducible R code, allowing readers to implement and extend the methods themselvesIntuitive figures and visual explanations that clarify abstract conceptsBroad coverage of applications within statistics and data science, connecting rigorous theory with modern machine learning and causal inference 199 pp. Englisch. N° de réf. du vendeur 9789819542666
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Graphical Models and Causal Discovery with R
Edité par
Springer Verlag GmbH, 2026
ISBN 10 : 9819542669
ISBN 13 : 9789819542666
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. N° de réf. du vendeur 2647691217
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Graphical Models and Causal Discovery with R : 100 Exercises for Building Logic
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical inference, and graph theory, the book offers a systematic pathway from foundational principles to cutting-edge algorithms, including independence tests, the PC algorithm, LiNGAM, information criteria, and Bayesian methods. Far more than a theoretical treatment, this volume emphasizes hands-on learning through R implementations, carefully designed exercises with solutions, and intuitive graphical illustrations. Readers will gain the ability to see, run, and understand causal discovery methods in practice.Key features of this book include:A clear and self-contained introduction, bridging probability, statistics, and modern causal discovery techniques100 exercises with solutions, supporting self-study and classroom useReproducible R code, allowing readers to implement and extend the methods themselvesIntuitive figures and visual explanations that clarify abstract conceptsBroad coverage of applications within statistics and data science, connecting rigorous theory with modern machine learning and causal inference. N° de réf. du vendeur 9789819542666
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Graphical Models and Causal Discovery with R
Edité par
Springer, Springer Mai 2026, 2026
ISBN 10 : 9819542669
ISBN 13 : 9789819542666
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical inference, and graph theory, the book offers a systematic pathway from foundational principles to cutting-edge algorithms, including independence tests, the PC algorithm, LiNGAM, information criteria, and Bayesian methods. Far more than a theoretical treatment, this volume emphasizes hands-on learning through R implementations, carefully designed exercises with solutions, and intuitive graphical illustrations. Readers will gain the ability to see, run, and understand causal discovery methods in practice.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 212 pp. Englisch. N° de réf. du vendeur 9789819542666
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Graphical Models and Causal Discovery with R | 100 Exercises for Building Logic
Vendeur : preigu, Osnabrück, Allemagne
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Taschenbuch. Etat : Neu. Graphical Models and Causal Discovery with R | 100 Exercises for Building Logic | Joe Suzuki | Taschenbuch | xii | Englisch | 2026 | Springer | EAN 9789819542666 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 134945973
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