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Añadir al carritoPaperback. Condición: Fair. No Jacket. Former library book; Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less 0.75.
Publicado por Springer, Use R !, 2010
Librería: Rometti Vincent, Nice, Francia
EUR 35,00
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Añadir al carritoCouverture souple. Condición: Très bon. Springer, Use R !, 2010. In-8 broché, XIX+283pp. Très bon état.
Publicado por New York. Springer. 2010., 2009
ISBN 10: 1441915753 ISBN 13: 9781441915757
Idioma: Inglés
Librería: Antiquariat am Flughafen, Berlin, Alemania
EUR 49,95
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Añadir al carritoSoftcover. Condición: sehr gut. Softcover. gr. 8°. xix, 283 pages. with illustrations and tables. less marks of use. good condition. Series Use R!". in englischer Sprache (in english).
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 81,41
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EUR 74,77
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Librería: SGS Trading Inc, Franklin Lakes, NJ, Estados Unidos de America
EUR 62,21
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Añadir al carritoPaperback. Condición: Good. Textbook, May Have Highlights, Notes and/or Underlining, BOOK ONLYNO ACCESS CODE, NO CD, Ships with Emailed Tracking.
EUR 79,75
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing Monte Carlo Methods with R covers the main tools used in statistical simulation from a programmer's point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison. While this book constitutes a comprehensive treatment of simulation methods, the theoretical justification of those methods has been considerably reduced, compared with Robert and Casella (2004). Similarly, the more exploratory and less stable solutions are not covered here.This book does not require a preliminary exposure to the R programming language or to Monte Carlo methods, nor an advanced mathematical background. While many examples are set within a Bayesian framework, advanced expertise in Bayesian statistics is not required. The book covers basic random generation algorithms, Monte Carlo techniques for integration and optimization, convergence diagnoses, Markov chain Monte Carlo methods, including Metropolis {Hastings and Gibbs algorithms, and adaptive algorithms. All chapters include exercises and all R programs are available as an R package called mcsm. The book appeals to anyone with a practical interest in simulation methods but no previous exposure. It is meant to be useful for students and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The programming parts are introduced progressively to be accessible to any reader.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 87,88
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EUR 77,80
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 78,58
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Librería: HPB-Red, Dallas, TX, Estados Unidos de America
EUR 20,88
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Añadir al carritoPaperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 77,37
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EUR 138,49
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 128,69
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 160,79
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Publicado por SPRINGER NATURE Dez 2009, 2009
ISBN 10: 1441915753 ISBN 13: 9781441915757
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 74,89
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing Monte Carlo Methods with R covers the main tools used in statistical simulation from a programmer's point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison. While this book constitutes a comprehensive treatment of simulation methods, the theoretical justification of those methods has been considerably reduced, compared with Robert and Casella (2004). Similarly, the more exploratory and less stable solutions are not covered here.This book does not require a preliminary exposure to the R programming language or to Monte Carlo methods, nor an advanced mathematical background. While many examples are set within a Bayesian framework, advanced expertise in Bayesian statistics is not required. The book covers basic random generation algorithms, Monte Carlo techniques for integration and optimization, convergence diagnoses, Markov chain Monte Carlo methods, including Metropolis {Hastings and Gibbs algorithms, and adaptive algorithms. All chapters include exercises and all R programs are available as an R package called mcsm. The book appeals to anyone with a practical interest in simulation methods but no previous exposure. It is meant to be useful for students and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The programming parts are introduced progressively to be accessible to any reader. 284 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 66,44
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book to present modern Monte Carlo and Markov Chain Monte Carlo (MCMC) methods from a practical perspective through a guided implementation in the R languageAll concepts are carefully described with the abstract theoretical background re.
Publicado por Springer-Verlag New York Inc., 2009
ISBN 10: 1441915753 ISBN 13: 9781441915757
Idioma: Inglés
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 92,72
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 471.