Radu Craiu (27 results)
Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 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)
Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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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)
Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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hardcover. Condition: New.
Language: English
Published by CRC Press, 2026
Series: Book 3 of 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)
Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 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)
Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Condition: New. 2026. 2nd Edition. hardcover. . . . . .
Language: English
Published by Taylor and Francis Ltd, GB, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
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Hardback. Condition: 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… 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.
Language: English
Published by Taylor and Francis Ltd, GB, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardback. Condition: 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… 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.
Language: English
Published by Chapman and Hall/CRC, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condition: New. 2026. 2nd Edition. hardcover. . . . . . Books ship from the US and Ireland.
Language: English
Published by CRC Press, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: moluna, Greven, Germanymoluna
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Condition: 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.
Language: English
Published by Taylor & Francis Ltd Mär 2026, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: 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…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 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.
Language: English
Published by Taylor and Francis Ltd, GB, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
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Hardback. Condition: 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… 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.
Language: English
Published by TAYLOR & FRANCIS NP EXCLUSIVE(CBS), 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- International Edition
Seller: UK BOOKS STORE, London, LONDO, United KingdomUK BOOKS STORE
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Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if th…e Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Language: English
Published by Taylor & Francis Ltd, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: preigu, Osnabrück, Germanypreigu
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Buch. Condition: 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.
Language: English
Published by Taylor and Francis Ltd, GB, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Hardback. Condition: 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… 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.
Language: English
Published by Chapman & Hall, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 2nd edition. 680 pages. 10.00x7.00x10.00 inches. In Stock.
Language: English
Published by Taylor & Francis Ltd, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
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Hardcover. Condition: 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 o…ffers 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.
Language: English
Published by Chapman & Hall, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print on Demand
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 2nd edition. 680 pages. 10.00x7.00x10.00 inches. In Stock. This item is printed on demand.
Language: English
Published by Taylor & Francis Ltd, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print on Demand
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Hardcover. Condition: 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 o…ffers 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.
Language: English
Published by Taylor & Francis Ltd, 2026
Series: Book 3 of 27 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods
- Hardcover
- Print on Demand
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Hardcover. Condition: 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 o…ffers 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.
