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ThriftBooks-Dallas, Dallas, TX, Etats-Unis
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Former library book; Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less 0.75. N° de réf. du vendeur G1441915753I5N10
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.
Présentation de l'éditeur:
This book 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.
Titre : Introducing Monte Carlo Methods with R
Éditeur : Springer
Date d'édition : 2009
Reliure : Paperback
Etat : Fair
Etat de la jaquette : No Jacket
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
Paperback. Etat : 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! N° de réf. du vendeur S_429651912
Quantité disponible : 1 disponible(s)
Vendeur : Evergreen Goodwill, Seattle, WA, Etats-Unis
paperback. Etat : Good. N° de réf. du vendeur mon0000357923
Quantité disponible : 1 disponible(s)
Vendeur : Good Reading Secondhand Books, Benalla, VIC, Australie
Soft cover. Etat : Fine. xv 283 pages. Apart from minor shelf wear the book appears untouched. '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." (Publisher). N° de réf. du vendeur 019453
Quantité disponible : 1 disponible(s)
Vendeur : HPB Inc., Dallas, TX, Etats-Unis
paperback. Etat : Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_454038305
Quantité disponible : 1 disponible(s)
Vendeur : GoldBooks, Denver, CO, Etats-Unis
Etat : new. N° de réf. du vendeur 84V96_33_1441915753
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 7725631-n
Quantité disponible : 4 disponible(s)
Vendeur : Speedyhen, London, Royaume-Uni
Etat : NEW. N° de réf. du vendeur NW9781441915757
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 7725631
Quantité disponible : 4 disponible(s)
Vendeur : Brook Bookstore, Milano, MI, Italie
Etat : new. N° de réf. du vendeur 87f546bdf647be62b86cc7c4a8b614a3
Quantité disponible : 5 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 7725631-n
Quantité disponible : Plus de 20 disponibles