Monte Carlo Statistical Methods

Name: Monte Carlo Statistical Methods
Brand: Springer-Verlag New York Inc.
SKU: 9780387212395
Price: 75349 HUF
Availability: InStock

Szerző: George Casella, Christian Robert

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer-Verlag New York Inc.

Elérhetőség: Beszállítói készleten

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Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential com...

Információk a könyvről

Szerző

George Casella, Christian Robert

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2005

oldal

649

EAN

9780387212395

ISBN

0387212396

Enbook ID

01380945

Kiadó

Springer-Verlag New York Inc.

Súly

1172

Méretek

165 x 236 x 43

Teljes leírás

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.

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Monte Carlo Statistical Methods

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