Lingua: Inglese
Editore: Cambridge University Press, 2021
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Lingua: Inglese
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Lingua: Inglese
Editore: Cambridge University Press, 2021
ISBN 10: 1316610853 ISBN 13: 9781316610855
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ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloPaperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Paperback. Condizione: new. Paperback. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Editore: Cambridge University Press, 2021
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Lingua: Inglese
Editore: Cambridge University Press, GB, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Paperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.
Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Lingua: Inglese
Editore: Cambridge University Press, 2021
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloPaperback. Condizione: Brand New. 291 pages. 8.75x6.00x0.75 inches. In Stock.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, 2021
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloCondizione: New. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced und.
Lingua: Inglese
Editore: Cambridge University Press, GB, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
Paperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.
Lingua: Inglese
Editore: Cambridge University Press Nov 2020, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.
Lingua: Inglese
Editore: Cambridge University Press, Cambridge, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Cambridge University Press, GB, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloPaperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.
Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1316610853 ISBN 13: 9781316610855
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Inferential Network Analysis | Skyler J Cranmer (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2020 | Cambridge University Press | EAN 9781316610855 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.