9780387212395 - monte carlo statistical methods (springer texts in statistics) de christian robert (18 resultados)
Idioma: Inglés
Editorial: Springer (edition 2nd), 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: BooksRun, Philadelphia, PA, Estados Unidos de AmericaBooksRun
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Hardcover. Condición: Very Good. 2nd. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Boards & Wraps, Baltimore, MD, Estados Unidos de AmericaBoards & Wraps
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EUR 67,66
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Hardcover. Condición: Very Good. Second Edition. Covers clean and unmarked, interior clean, tight, and unmarked. Slight bumping of corners, spine faded. Owner's name inscribed on FFEP. International shipping billed at cost. Photos upon request.; Springer Texts In Statistics; 6.5 X 1.7 X 9.3 inches; 679 pages.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Textbooks_Source, Columbia, MO, Estados Unidos de AmericaTextbooks_Source
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hardcover. Condición: Good. 2nd. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: medimops, Berlin, Alemaniamedimops
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Condición: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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Condición: As New. Unread book in perfect condition.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Brook Bookstore, Milano, MI, ItaliaBrook Bookstore
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Condición: new.
Idioma: Inglés
Editorial: Springer Verlag, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 191,01
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Hardcover. Condición: Brand New. 2nd edition. 645 pages. 9.50x6.50x1.50 inches. In Stock.
Idioma: Inglés
Editorial: Springer-Verlag New York Inc., New York, NY, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 209,74
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Hardcover. Condición: new. Hardcover. Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of…the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation There are five completely new chapters that cover Monte Carlo control, reversible jump, slice sampling, sequential Monte Carlo, and perfect sampling. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters. The development of Gibbs sampling starts with slice sampling and its connection with the fundamental theorem of simulation, and builds up to two-stage Gibbs sampling and its theoretical properties. A third chapter covers the multi-stage Gibbs sampler and its variety of applications. Lastly, chapters from the previous edition have been revised towards easier access, with the examples getting more detailed coverage. This textbook is intended for a second year graduate course, but will also be useful to someone who either wants to apply simulation techniques for the resolution of practical problems or wishes to grasp the fundamental principles behind those methods. The authors do not assume familiarity with Monte Carlo techniques (such as random variable generation), with computer programming, or with any Markov chain theory (the necessary concepts are developed in Chapter 6). A solutions manual, which covers approximately 40% of the problems, is available for instructors who require the book for a course. Christian P. Robert is Professor of Statistics in the Applied Mathematics Department at Universite Paris Dauphine, France. He is also Head of the Statistics Laboratoryat the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris, and Adjunct Professor at Ecole Polytechnique. He has written three other books and won the 2004 DeGroot Prize for The Bayesian Choice, Second Edition, Springer 2001. He also edited Discretization and MCMC Convergence Assessment, Springer 1998. He has served as associate editor for the Annals of Statistics, Statistical Science and the Journal of the American Statistical Association. He is a fellow of the Institute of Mathematical Statistics, and a winner of the Young Statistician Award of the Societe de Statistique de Paris in 1995. George Casella is Distinguished Professor and Chair, Department of Statistics, University of Florida. He has served as the Theory and Methods Editor of the Journal of the American Statistical Association and Executive Editor of Statistical Science. He has authored three other textbooks: Statistical Inference, Second Edition, 2001, with Roger L. Berger; Theory of Point Estimation, 1998, with Erich Lehmann; and Variance Components, 1992, with Shayle R. Searle and Charles E. McCulloch. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an elected fellow of the International Statistical Institute. Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 207,38
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Condición: New.
Idioma: Inglés
Editorial: Springer New York, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: moluna, Greven, Alemaniamoluna
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EUR 175,51
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Gebunden. Condición: New.
Idioma: Inglés
Editorial: Springer, Humana, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 219,37
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulati…on techniques, with incorporation of the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation There are five completely new chapters that cover Monte Carlo control, reversible jump, slice sampling, sequential Monte Carlo, and perfect sampling. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters. The development of Gibbs sampling starts with slice sampling and its connection with the fundamental theorem of simulation, and builds up to two-stage Gibbs sampling and its theoretical properties. A third chapter covers the multi-stage Gibbs sampler and its variety of applications. Lastly, chapters from the previous edition have been revised towards easier access, with the examples getting more detailed coverage. This textbook is intended for a second year graduate course, but will also be useful to someone who either wants to apply simulation techniques for the resolution of practical problems or wishes to grasp the fundamental principles behind those methods. The authors do not assume familiarity with Monte Carlo techniques (such as random variable generation), with computer programming, or with any Markov chain theory (the necessary concepts are developed in Chapter 6). A solutions manual, which covers approximately 40% of the problems, is available for instructors who require the book for a course. Christian P. Robert is Professor of Statistics in the Applied Mathematics Department at Université Paris Dauphine, France. He is also Head of the Statistics Laboratoryat the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris, and Adjunct Professor at Ecole Polytechnique. He has written three other books and won the 2004 DeGroot Prize for The Bayesian Choice, Second Edition, Springer 2001. He also edited Discretization and MCMC Convergence Assessment, Springer 1998. He has served as associate editor for the Annals of Statistics, Statistical Science and the Journal of the American Statistical Association. He is a fellow of the Institute of Mathematical Statistics, and a winner of the Young Statistician Award of the Société de Statistique de Paris in 1995. George Casella is Distinguished Professor and Chair, Department of Statistics, University of Florida. He has served as the Theory and Methods Editor of the Journal of the American Statistical Association and Executive Editor of Statistical Science. He has authored three other textbooks: Statistical Inference, Second Edition, 2001, with Roger L. Berger; Theory of Point Estimation, 1998, with Erich Lehmann; and Variance Components, 1992, with Shayle R. Searle and Charles E. McCulloch. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an elected fellow of the International Statistical Institute.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 292,88
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Condición: New. pp. 686 2nd Printing.
Idioma: Inglés
Editorial: Springer Verlag, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 312,08
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Hardcover. Condición: Brand New. 2nd edition. 645 pages. 9.50x6.50x1.50 inches. In Stock.
Idioma: Inglés
Editorial: Springer-Verlag New York Inc., New York, NY, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Hardcover. Condición: new. Hardcover. Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of…the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation There are five completely new chapters that cover Monte Carlo control, reversible jump, slice sampling, sequential Monte Carlo, and perfect sampling. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters. The development of Gibbs sampling starts with slice sampling and its connection with the fundamental theorem of simulation, and builds up to two-stage Gibbs sampling and its theoretical properties. A third chapter covers the multi-stage Gibbs sampler and its variety of applications. Lastly, chapters from the previous edition have been revised towards easier access, with the examples getting more detailed coverage. This textbook is intended for a second year graduate course, but will also be useful to someone who either wants to apply simulation techniques for the resolution of practical problems or wishes to grasp the fundamental principles behind those methods. The authors do not assume familiarity with Monte Carlo techniques (such as random variable generation), with computer programming, or with any Markov chain theory (the necessary concepts are developed in Chapter 6). A solutions manual, which covers approximately 40% of the problems, is available for instructors who require the book for a course. Christian P. Robert is Professor of Statistics in the Applied Mathematics Department at Universite Paris Dauphine, France. He is also Head of the Statistics Laboratoryat the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris, and Adjunct Professor at Ecole Polytechnique. He has written three other books and won the 2004 DeGroot Prize for The Bayesian Choice, Second Edition, Springer 2001. He also edited Discretization and MCMC Convergence Assessment, Springer 1998. He has served as associate editor for the Annals of Statistics, Statistical Science and the Journal of the American Statistical Association. He is a fellow of the Institute of Mathematical Statistics, and a winner of the Young Statistician Award of the Societe de Statistique de Paris in 1995. George Casella is Distinguished Professor and Chair, Department of Statistics, University of Florida. He has served as the Theory and Methods Editor of the Journal of the American Statistical Association and Executive Editor of Statistical Science. He has authored three other textbooks: Statistical Inference, Second Edition, 2001, with Roger L. Berger; Theory of Point Estimation, 1998, with Erich Lehmann; and Variance Components, 1992, with Shayle R. Searle and Charles E. McCulloch. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an elected fellow of the International Statistical Institute. Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Idioma: Inglés
Editorial: Springer, Springer Jul 2004, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage o…f these simulation techniques, with incorporation of the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation There are five completely new chapters that cover Monte Carlo control, reversible jump, slice sampling, sequential Monte Carlo, and perfect sampling. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters. The development of Gibbs sampling starts with slice sampling and its connection with the fundamental theorem of simulation, and builds up to two-stage Gibbs sampling and its theoretical properties. A third chapter covers the multi-stage Gibbs sampler and its variety of applications. Lastly, chapters from the previous edition have been revised towards easier access, with the examples getting more detailed coverage. This textbook is intended for a second year graduate course, but will also be useful to someone who either wants to apply simulation techniques for the resolution of practical problems or wishes to grasp the fundamental principles behind those methods. The authors do not assume familiarity with Monte Carlo techniques (such as random variable generation), with computer programming, or with any Markov chain theory (the necessary concepts are developed in Chapter 6). A solutions manual, which covers approximately 40% of the problems, is available for instructors who require the book for a course. Christian P. Robert is Professor of Statistics in the Applied Mathematics Department at Université Paris Dauphine, France. He is also Head of the Statistics Laboratoryat the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris, and Adjunct Professor at Ecole Polytechnique. He has written three other books and won the 2004 DeGroot Prize for The Bayesian Choice, Second Edition, Springer 2001. He also edited Discretization and MCMC Convergence Assessment, Springer 1998. He has served as associate editor for the Annals of Statistics, Statistical Science and the Journal of the American Statistical Association. He is a fellow of the Institute of Mathematical Statistics, and a winner of the Young Statistician Award of the Société de Statistique de Paris in 1995. George Casella is Distinguished Professor and Chair, Department of Statistics, University of Florida. He has served as the Theory and Methods Editor of the Journal of the American Statistical Association and Executive Editor of Statistical Science. He has authored three other textbooks: Statistical Inference, Second Edition, 2001, with Roger L. Berger; Theory of Point Estimation, 1998, with Erich Lehmann; and Variance Components, 1992, with Shayle R. Searle and Charles E. McCulloch. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an elected fellow of the International Statistical Institute. 684 pp. Englisch.
Idioma: Inglés
Editorial: Springer, Humana Jul 2004, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -From the reviews of the first edition:'Although the book is written as a textbook, with many carefully worked out examples and exercises, it will be very useful for the researcher since the authors discuss their favorite research topics (Monte… Carlo optimization and convergence diagnostics) going through many relevant references.This book is a comprehensive treatment of the subject and will be an essential reference for statisticians working with McMC.' -Mathematical ReviewsSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 684 pp. Englisch.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Condición: New. Print on Demand pp. 686 Illus. This item is printed on demand.
Idioma: Inglés
Editorial: Springer, 2004
Serie: Springer Texts in Statistics, Libro 46 de 111. Libro 46 de 111 - Springer Texts in Statistics
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND pp. 686.
