Isbn: 9781498788625 - handbook of graphical models (chapman & hall/crc handbooks of modern statistical methods) (18 resultados)

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Hardcover. Condición: new. Hardcover. A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference.While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art.Key features:* Contributions by leading researchers from a range of disciplines* Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications* Balanced coverage of concepts, theory, methods, examples, and applications* Chapters can be read mostly independently, while cross-references highlight connectionsThe handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models. While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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Hardcover. Condición: Brand New. 536 pages. 10.00x7.25x1.25 inches. In Stock.

Hardcover. Condición: new. Hardcover. A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference.While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art.Key features:* Contributions by leading researchers from a range of disciplines* Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications* Balanced coverage of concepts, theory, methods, examples, and applications* Chapters can be read mostly independently, while cross-references highlight connectionsThe handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models. While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A graphical model is a statistical model that isrepresented bya graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference.While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art.Key features:\* Contributions by leading researchers from a range of disciplines\* Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications\* Balanced coverage of concepts, theory, methods, examples, and applications\* Chapters can be read mostly independently, while cross-references highlight connectionsThe handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models. 556 pp. Englisch.…

Hardcover. Condición: Brand New. 536 pages. 10.00x7.25x1.25 inches. In Stock. This item is printed on demand.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Marloes Maathuis is Professor of Statistics at ETH Zurich.Mathias Drton is Professor of Statistics at the University of Copenhagen and the University of Washington.Steffen Lauritzen is Prof.…

Buch. Condición: Neu. Handbook of Graphical Models | Marloes Maathuis (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2018 | CRC Press | EAN 9781498788625 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu Print on Demand.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A graphical model is a statistical model that isrepresented bya graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference.While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art.Key features:\* Contributions by leading researchers from a range of disciplines\* Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications\* Balanced coverage of concepts, theory, methods, examples, and applications\* Chapters can be read mostly independently, while cross-references highlight connectionsThe handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.…