A comprehensive introduction to sampling-based methods in statistical computing
The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods.
An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques
An Introduction to Statistical Computing
This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Jochen Voss, School of Mathematics, University of Leeds, UK.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : New. A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. Series: Wiley Series in Computational Statistics. Num Pages: 396 pages, black & white illustrations, black & white tables, figures. BIC Classification: PBT; UYM. Category: (P) Professional & Vocational. Dimension: 160 x 230 x 23. Weight in Grams: 636. . 2013. 1st Edition. Hardcover. . . . . N° de réf. du vendeur V9781118357729
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