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Introducing Monte Carlo Methods with R (Record no. 22809)

000 -LEADER
fixed length control field 05491nam a22005295i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310151444.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
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fixed length control field 100301s2010 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781441915764
978-1-4419-1576-4
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
264 #1 -
-- New York, NY :
-- Springer New York,
-- 2010.
912 ## -
-- ZDB-2-SMA
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Robert, Christian.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Introducing Monte Carlo Methods with R
Medium [electronic resource] /
Statement of responsibility, etc by Christian Robert, George Casella.
300 ## - PHYSICAL DESCRIPTION
Extent XX, 284 p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Use R
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Basic R Programming -- Random Variable Generation -- Monte Carlo Integration -- Controlling and Accelerating Convergence -- Monte Carlo Optimization -- Metropolis–Hastings Algorithms -- Gibbs Samplers -- Convergence Monitoring and Adaptation for MCMC Algorithms.
520 ## - SUMMARY, ETC.
Summary, etc 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. Christian P. Robert is Professor of Statistics at Université Paris Dauphine, and Head of the Statistics Laboratory of CREST, both in Paris, France. He has authored more than 150 papers in applied probability, Bayesian statistics and simulation methods. He is a fellow of the Institute of Mathematical Statistics and the recipient of an IMS Medallion. He has authored eight other books, including The Bayesian Choice which received the ISBA DeGroot Prize in 2004, Monte Carlo Statistical Methods with George Casella, and Bayesian Core with Jean-Michel Marin. He has served as Joint Editor of the Journal of the Royal Statistical Society Series B, as well as an associate editor for most major statistical journals, and was the 2008 ISBA President. George Casella is Distinguished Professor in the Department of Statistics at the University of Florida. He is active in both theoretical and applied statistics, is a fellow of the Institute of Mathematical Statistics and the American Statistical Association, and a Foreign Member of the Spanish Royal Academy of Sciences. He has served as Theory and Methods Editor of the Journal of the American Statistical Association, as Executive Editor of Statistical Science, and as Joint Editor of the Journal of the Royal Statistical Society Series B. In addition to books with Christian Robert, he has written Variance Components, 1992, with S.R. Searle and C.E. McCulloch; Statistical Inference, Second Edition, 2001, with Roger Berger; and Theory of Point Estimation, Second Edition, 1998, with Erich Lehmann. His latest book is Statistical Design 2008.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Computer simulation.
Topical term or geographic name as entry element Computer science
General subdivision Mathematics.
Topical term or geographic name as entry element Distribution (Probability theory).
Topical term or geographic name as entry element Mathematical statistics.
Topical term or geographic name as entry element Engineering mathematics.
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Statistics and Computing/Statistics Programs.
Topical term or geographic name as entry element Simulation and Modeling.
Topical term or geographic name as entry element Computational Mathematics and Numerical Analysis.
Topical term or geographic name as entry element Probability and Statistics in Computer Science.
Topical term or geographic name as entry element Appl.Mathematics/Computational Methods of Engineering.
Topical term or geographic name as entry element Probability Theory and Stochastic Processes.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Casella, George.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781441915757
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4419-1576-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-09AUM Main Library2014-04-09 2014-04-09 E-Book   AUM Main Library519.5
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