Vous voulez voir cette page en français ? Cliquez ici.


or
Sign in to turn on 1-Click ordering.
More Buying Choices
Have one to sell? Sell yours here
Monte Carlo Statistical Methods
 
 

Monte Carlo Statistical Methods [Hardcover]

Christian Robert , George Casella
4.7 out of 5 stars  See all reviews (3 customer reviews)
List Price: CDN$ 117.95
Price: CDN$ 94.36 & this item ships for FREE with Super Saver Shipping. Details
You Save: CDN$ 23.59 (20%)
o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o
In Stock.
Ships from and sold by Amazon.ca. Gift-wrap available.
Only 1 left in stock--order soon (more on the way).
Want it delivered Tuesday, May 29? Choose One-Day Shipping at checkout.

Formats

Amazon Price New from Used from
Hardcover CDN $94.36  
Paperback CDN $92.35  

Product Details


Product Description

Review

From the reviews: MATHEMATICAL REVIEWS "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." From the reviews of the second edition: "Only 2 years after its first edition this carefully revised second edition accounts for the rapid development in this field...This book can be highly recommended for students and researchers interested in learning more about MCMC methods and their background." Biometrics, March 2005 "This is a comprehensive book for advanced graduate study by statisticians." Technometrics, May 2005 "This excellent text is highly recommended..." Short Book Reviews of the ISI, April 2005 "This book provides a thorough introduction to Monte Carlo methods in statistics with an emphasis on Markov chain Monte Carlo methods. … Each chapter is concluded by problems and notes. … The book is self-contained and does not assume prior knowledge of simulation or Markov chains. …. on the whole it is a readable book with lots of useful information." (Søren Feodor Nielsen, Journal of Applied Statistics, Vol. 32 (6), August, 2005) "This revision of the influential 1999 text … includes changes to the presentation in the early chapters and much new material related to MCMC and Gibbs sampling. The result is a useful introduction to Monte Carlo methods and a convenient reference for much of current methodology. … The numerous problems include many with analytical components. The result is a very useful resource for anyone wanting to understand Monte Carlo procedures. This excellent text is highly recommended … ." (D.F. Andrews, Short Book Reviews, Vol. 25 (1), 2005) "You have to practice statistics on a desert island not to know that Markov chain Monte Carlo (MCMC) methods are hot. That situation has caused the authors not only to produce a new edition of their landmark book but also to completely revise and considerably expand it. … This is a comprehensive book for advanced graduate study by statisticians." (Technometrics, Vol. 47 (2), May, 2005) "This remarkable book presents a broad and deep coverage of the subject. … This second edition is a considerably enlarged version of the first. Some subjects that have matured more rapidly in the five years following the first edition, like reversible jump processes, sequential MC, two-stage Gibbs sampling and perfect sampling have now chapters of their own. … the book is also very well suited for self-study and is also a valuable reference for any statistician who wants to study and apply these techniques." (Ricardo Maronna, Statistical Papers, Vol. 48, 2006) "This second edition of ‘Monte Carlo Statistical Methods’ has appeared only five years after the first … the new edition aims to incorporate recent developments. … Each chapter includes sections with problems and notes. … The style of the presentation and many carefully designed examples make the book very readable and easily accessible. It represents a comprehensive account of the topic containing valuable material for lecture courses as well as for research in this area." (Evelyn Buckwar, Zentrablatt MATH, Vol. 1096 (22), 2006) "This is a useful and utilitarian book. It provides a catalogue of modern Monte carlo based computational techniques with ultimate emphasis on Markov chain Monte Carlo (MCMC) … . an excellent reference for anyone who is interested in algorithms for various modes of Markov chain (MC) methodology … . a must for any researcher who believes in the importance of understanding what goes on inside of the MCMC ‘black box.’ … I recommend the book to all who wish to learn about statistical simulation." (Wesley O. Johnson, Journal of the American Statistical Association, Vol. 104 (485), March, 2009)

Book Description

We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

Inside This Book (Learn More)
First Sentence
 Read the first page
Explore More
Concordance
Browse Sample Pages
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Search inside this book:

Tag this product

 (What's this?)
Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organize and find favorite items.
Your tags: Add your first tag
 

What Other Items Do Customers Buy After Viewing This Item?


 

Customer Reviews

3 Reviews
5 star:
 (2)
4 star:
 (1)
3 star:    (0)
2 star:    (0)
1 star:    (0)
 
 
 
 
 
Average Customer Review
4.7 out of 5 stars (3 customer reviews)
 
 
 
 
Share your thoughts with other customers:
Most helpful customer reviews

4.0 out of 5 stars Modern text on Monte Carlo with a Bayesian Perspective, Mar 30 2000
By 
Michael R. Chernick "statman13" (Malvern, PA) - See all my reviews
(REAL NAME)   
Monte Carlo methods are old. They can be traced back to Buffon's needle problem in the 17th century. However meaningful application had to wait for the invention of digital computers in the 20th century. Much of the development took place in the 1940s and 50s for military and nuclear engineering application. The Hastings - Metropolis algorithm of the 1950s has had a rebirth in the 1990s with the application of Markov Chain Monte Carlo methods to imaging problems and many Bayesian problems.

The authors of this book are Bayesians and present Bayesian methods in the very first chapter. The book is intended to be a course text on Monte Carlo methods. I judge the level to be intermediate to advanced (first or second year graduate level). The first chapter introduces statistical and numerical problems that Monte Carlo methods can solve. It includes a discussion of bootstrap methods in the notes at the end of the chapter. Chapters 2 and 3 introduce standard topics including methods for generating pseudo-random numbers and various variance reduction techniques. Chapter 4 is an introduction to Markov Chains. Markov Chains are commonly a topic in introductory courses on stochastic processes. The authors presuppose that the reader has no knowledge of Markov Chains. So they develop the essential aspects of the theory needed in the application of Markov Chain Monte Carlo methods (MCMC). Chapter 5 then deals with optimization problems discussing simulated annealing, stochastic approximation and the EM algorithm. Chapters 6 - 8 deal with topic in MCMC methods. The final chapter deals with applications to missing data models. The topics are very current and important to statisticians. The theory is covered very well. Many interesting examples are provided throughout the book. A number of these are presented in the problems section at the end of the chapters. It also contains a very extensive bibliography.

Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


2 of 2 people found the following review helpful
5.0 out of 5 stars Does something necessary, does it well., Dec 9 2002
By A Customer
This text may or may not be the best book on MC for a particular application; to be honest, it's the only book on MC I own.

However, I did peruse a number of texts before I bought this one, and I am very pleased with my decision. To me, this book does something that seems necessary but is relatively uncommon: it gives a detailed, modern, comprehensive introduction to MC methods per se. There are other texts that might have one of those characteristics, but they seem to either not have all of them: they either are not modern, not comprehensive, not introductory, or are not concerned with Monte Carlo per se.

Many other excellent texts, for example, are largely oriented toward Bayesian implementations, or general integration, but not both.

I would highly recommend this book as an excellent introduction to MC methods as a general computational tool.

Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


2 of 3 people found the following review helpful
5.0 out of 5 stars Useful and Clear, Feb 15 2003
By A Customer
I have a graduate level physics and mathematics background really enjoyed the clear descriptions as a useful and ever-needed review.

Monte Carlo experts who want to apply their knowlege to finance should also read: "Options, Futures, and Other Derivatives (5th Edition) by John Hull; and "Credit Derivatives" (2nd Edition) by Janet Tavakoli.

Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No

Share your thoughts with other customers: Create your own review
Want to see more reviews on this item?
 Go to Amazon.com to see all 8 reviews  4.2 out of 5 stars 
 
 
Only search this product's reviews



Listmania!

Create a Listmania! list

Look for similar items by category


Look for similar items by subject


Feedback


Amazon.ca Privacy Statement Amazon.ca Shipping Information Amazon.ca Returns & Exchanges