ISBN: 9780198739074 - bayesian theory and applications (22 risultati)

Condizione: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

paperback. Condizione: Very Good.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. No phenomenon in any aspect of human enterprise is known with certainty. Probability and Statistics help us quantify uncertainty and lead to better decisions that, hopefully, enhance life. The impact of the ideas in this book has already revolutionised our ability to take informed decisions, and continues to do so at an astonishing rate. Editor(s): Damien, Paul; Dellaportas, Petros; Polson, Nicholas G.; Stephens, David A. Num Pages: 718 pages, 121 b/w line drawings & 21 b/w halftones. BIC Classification: PBT. Category: (UU) Undergraduate. Dimension: 235 x 155 x 40. Weight in Grams: 1050. . 2015. Paperback. . . . .…

Paperback. Condizione: New. The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics. …

Condizione: New. No phenomenon in any aspect of human enterprise is known with certainty. Probability and Statistics help us quantify uncertainty and lead to better decisions that, hopefully, enhance life. The impact of the ideas in this book has already revolutionised our ability to take informed decisions, and continues to do so at an astonishing rate. Editor(s): Damien, Paul; Dellaportas, Petros; Polson, Nicholas G.; Stephens, David A. Num Pages: 718 pages, 121 b/w line drawings & 21 b/w halftones. BIC Classification: PBT. Category: (UU) Undergraduate. Dimension: 235 x 155 x 40. Weight in Grams: 1050. . 2015. Paperback. . . . . Books ship from the US and Ireland.…

Paperback. Condizione: New. The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics. …

Condizione: new. Questo è un articolo print on demand.

Paperback. Condizione: new. Paperback. The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics.This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances inthis field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on theconcept.Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research.Hence, the audience for thisunique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation,business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy.The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him.Bayesian Theory andApplications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics. No phenomenon in any aspect of human enterprise is known with certainty. Probability and Statistics help us quantify uncertainty and lead to better decisions that, hopefully, enhance life. The impact of the ideas in this book has already revolutionised our ability to take informed decisions, and continues to do so at an astonishing rate. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condizione: new. Paperback. The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics.This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances inthis field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on theconcept.Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research.Hence, the audience for thisunique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation,business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy.The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him.Bayesian Theory andApplications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics. No phenomenon in any aspect of human enterprise is known with certainty. Probability and Statistics help us quantify uncertainty and lead to better decisions that, hopefully, enhance life. The impact of the ideas in this book has already revolutionised our ability to take informed decisions, and continues to do so at an astonishing rate. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. No phenomenon in any aspect of human enterprise is known with certainty. Probability and Statistics help us quantify uncertainty and lead to better decisions that, hopefully, enhance life. The impact of the ideas in this book has already revolutionised our .…

Paperback. Condizione: new. Paperback. The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics.This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances inthis field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on theconcept.Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research.Hence, the audience for thisunique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation,business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy.The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him.Bayesian Theory andApplications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics. No phenomenon in any aspect of human enterprise is known with certainty. Probability and Statistics help us quantify uncertainty and lead to better decisions that, hopefully, enhance life. The impact of the ideas in this book has already revolutionised our ability to take informed decisions, and continues to do so at an astonishing rate. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condizione: New. Print on Demand pp. 720.

Condizione: New. Print on Demand pp. 720.

Taschenbuch. Condizione: Neu. Bayesian Theory and Applications | Paul Damien (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2015 | OUP Oxford | EAN 9780198739074 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Condizione: New. PRINT ON DEMAND pp. 720.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics.…