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Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
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EUR 118,71
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Da: Majestic Books, Hounslow, Regno Unito
EUR 139,25
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EUR 131,29
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Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 149,99
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EUR 121,56
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Aggiungi al carrelloCondizione: New. Hang Qian is the principal engineer of the Econometrics Toolbox for MATLAB and has been dedicated to statistical software development at MathWorks since 2012. He earned his PhD in economics, specializing in Bayesian statistics, big data analysis, .
EUR 201,90
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Aggiungi al carrelloHardcover. Condizione: Brand New. 488 pages. 10.00x7.00x10.24 inches. In Stock.
Da: Majestic Books, Hounslow, Regno Unito
EUR 53,15
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 53,65
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Shanghai Jiao Tong University Press|Springer, 2021
ISBN 10: 9811559309 ISBN 13: 9789811559303
Da: moluna, Greven, Germania
EUR 32,41
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Drawing on the sun, moon, dragon, phoenix, Nuwa, Yandi, Huangdi and other widely circulated cultural elements as examples, this book addresses the development and evolution of the most representative Chinese creation myths regarding nature, totems, ancestor.
Da: moluna, Greven, Germania
EUR 32,41
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A masterpiece that gathers contributions by the most accomplished mythologists in China           The most representative source on Chinese creation myths to date  Employs a narrativ.
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques, seamlessly integrating these scalable methods into a broad spectrum of econometric models.In addition to its focus on big data, the book introduces novel concepts within traditional statistics, such as the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators conceptualize pseudo data in the conjugate prior, sufficient statistics that determine the likelihood, and the posterior as a balance between data and prior information, adding an intriguing dimension to Bayesian analysis. This book also offers a deep dive into Bayesian computation. Given the intricacies of floating-point representation of real numbers, computer programs can sometimes yield unexpected or theoretically impossible results. Drawing from his experience as a senior statistical software developer, the author shares valuable strategies for designing numerically stable algorithms.The book is an essential resource for a diverse audience: graduate students seeking foundational knowledge in Bayesian econometric models, early-career statisticians eager to explore cutting-edge advancements in scalable Bayesian methods, data analysts struggling with out-of-memory challenges in large datasets, and statistical software users and developers striving to program with efficiency and numerical stability. This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques. The book is an essential resource for graduate students, early-career statisticians, data analysts, and statistical software users and developers. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Chapman And Hall/CRC Jun 2025, 2025
ISBN 10: 1032915250 ISBN 13: 9781032915258
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 120,40
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques, seamlessly integrating these scalable methods into a broad spectrum of econometric models.In addition to its focus on big data, the book introduces novel concepts within traditional statistics, such as the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators conceptualize pseudo data in the conjugate prior, sufficient statistics that determine the likelihood, and the posterior as a balance between data and prior information, adding an intriguing dimension to Bayesian analysis. This book also offers a deep dive into Bayesian computation. Given the intricacies of floating-point representation of real numbers, computer programs can sometimes yield unexpected or theoretically impossible results. Drawing from his experience as a senior statistical software developer, the author shares valuable strategies for designing numerically stable algorithms.The book is an essential resource for a diverse audience: graduate students seeking foundational knowledge in Bayesian econometric models, early-career statisticians eager to explore cutting-edge advancements in scalable Bayesian methods, data analysts struggling with out-of-memory challenges in large datasets, and statistical software users and developers striving to program with efficiency and numerical stability. 488 pp. Englisch.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 152,52
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Aggiungi al carrelloHRD. 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.