Radu craiu (27 Ergebnisse)
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Handbook of Markov Chain Monte Carlo
Craiu, Radu V. (EDT); Vats, Dootika (EDT); Jones, Galin L. (EDT); Brooks, Steve (EDT); Gelman, Andrew (EDT)
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
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Handbook of Markov Chain Monte Carlo
Craiu, Radu V. (EDT); Vats, Dootika (EDT); Jones, Galin L. (EDT); Brooks, Steve (EDT); Gelman, Andrew (EDT)
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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hardcover. Zustand: New.
Sprache: Englisch
Verlag: CRC Press, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Handbook of Markov Chain Monte Carlo
Craiu, Radu V. (EDT); Vats, Dootika (EDT); Jones, Galin L. (EDT); Brooks, Steve (EDT); Gelman, Andrew (EDT)
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
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- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Handbook of Markov Chain Monte Carlo
Craiu, Radu V. (EDT); Vats, Dootika (EDT); Jones, Galin L. (EDT); Brooks, Steve (EDT); Gelman, Andrew (EDT)
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Zustand: New. 2026. 2nd Edition. hardcover. . . . . .
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardback. Zustand: New. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now offers deeper i…nsights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardback. Zustand: New. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now offers deeper i…nsights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling.
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Zustand: New. 2026. 2nd Edition. hardcover. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: CRC Press, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Zustand: New. Radu V. Craiu is a professor of statistics at the University of Toronto. His research interests are in computational methods in statistics, statistical inference, copula models, model selection procedures, and the use of statistical methods for sc.
Sprache: Englisch
Verlag: Taylor & Francis Ltd Mär 2026, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Buch. Zustand: Neu. Neuware - This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now offers de…eper insights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features: - Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advances - In-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theory - Comprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence bounds - Practical guidance on implementing MCMC algorithms on modern hardware and software platforms - Cutting-edge material on the integration of MCMC with deep learning and other machine learning approaches - Authoritative treatment of theoretical foundations alongside practical implementation strategies - Supplemented by a GitHub repository including sample chapters, code, and data This essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardback. Zustand: New. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now offers deeper i…nsights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling.
Sprache: Englisch
Verlag: TAYLOR & FRANCIS NP EXCLUSIVE(CBS), 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Internationale Ausgabe
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Sprache: Englisch
Verlag: Taylor & Francis Ltd, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Buch. Zustand: Neu. Handbook of Markov Chain Monte Carlo | Andrew Gelman (u. a.) | Buch | Chapman & Hall/CRC Handbooks of Modern Statistical Methods | Einband - fest (Hardcover) | Englisch | 2026 | Taylor & Francis Ltd | EAN 9781032591575 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at…]libri[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Chapman & Hall, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardcover. Zustand: Brand New. 2nd edition. 680 pages. 10.00x7.00x10.00 inches. In Stock.
Sprache: Englisch
Verlag: Taylor and Francis Ltd, GB, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardback. Zustand: New. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now offers deeper i…nsights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print-on-Demand
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Hardcover. Zustand: new. Hardcover. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now off…ers deeper insights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition, This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Sprache: Englisch
Verlag: Chapman & Hall, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print-on-Demand
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Hardcover. Zustand: Brand New. 2nd edition. 680 pages. 10.00x7.00x10.00 inches. In Stock. This item is printed on demand.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print-on-Demand
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Hardcover. Zustand: new. Hardcover. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now off…ers deeper insights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition, This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, 2026
Serie: Buch 3 von 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print-on-Demand
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Hardcover. Zustand: new. Hardcover. This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now off…ers deeper insights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restructured content with 13 updated chapters from the first edition and ten entirely new chapters reflecting the latest methodological advancesIn-depth coverage of recent breakthroughs in multi-modal sampling, intractable likelihood problems, and involutive MCMC theoryComprehensive exploration of unbiased MCMC methods, control variates, and rigorous convergence boundsPractical guidance on implementing MCMC algorithms on modern hardware and software platformsCutting-edge material on the integration of MCMC with deep learning and other machine learning approachesAuthoritative treatment of theoretical foundations alongside practical implementation strategiesSupplemented by a GitHub repository including sample chapters, code, and dataThis essential reference serves statisticians, computer scientists, physicists, data scientists, and researchers across disciplines who employ computational methods for Bayesian inference and stochastic simulation. Graduate students will find it an invaluable learning resource, while experienced practitioners will appreciate its balance of theoretical depth and practical implementation advice. Whether used as a comprehensive guide to current MCMC methodology or as a reference for specific advanced techniques, this handbook provides the definitive resource for anyone working at the intersection of Bayesian computation and modern statistical modeling. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition, 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.
