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Introduction to Probability Simulation and Gibbs Sampling with R (Record no. 22568)

000 -LEADER
fixed length control field 03999nam a22004215i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310151441.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
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fixed length control field 100528s2010 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780387687650
978-0-387-68765-0
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 Suess, Eric A.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Introduction to Probability Simulation and Gibbs Sampling with R
Medium [electronic resource] /
Statement of responsibility, etc by Eric A. Suess, Bruce E. Trumbo.
300 ## - PHYSICAL DESCRIPTION
Extent XIII, 307p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Use R ;
Volume number/sequential designation 0
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introductory Examples: Simulation, Estimation, and Graphics -- Generating Random Numbers -- Monte Carlo Integration and Limit Theorems -- Sampling from Applied Probability Models -- Screening Tests -- Markov Chains with Two States -- Examples of Markov Chains with Larger State Spaces -- to Bayesian Estimation -- Using Gibbs Samplers to Compute Bayesian Posterior Distributions -- Using WinBUGS for Bayesian Estimation -- Appendix: Getting Started with R.
520 ## - SUMMARY, ETC.
Summary, etc The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling. These initial chapters can be used for a non-Bayesian course in the simulation of applied probability models and Markov Chains. Chapters 8 through 10 give a brief introduction to Bayesian estimation and illustrate the use of Gibbs samplers to find posterior distributions and interval estimates, including some examples in which traditional methods do not give satisfactory results. WinBUGS software is introduced with a detailed explanation of its interface and examples of its use for Gibbs sampling for Bayesian estimation. No previous experience using R is required. An appendix introduces R, and complete R code is included for almost all computational examples and problems (along with comments and explanations). Noteworthy features of the book are its intuitive approach, presenting ideas with examples from biostatistics, reliability, and other fields; its large number of figures; and its extraordinarily large number of problems (about a third of the pages), ranging from simple drill to presentation of additional topics. Hints and answers are provided for many of the problems. These features make the book ideal for students of statistics at the senior undergraduate and at the beginning graduate levels. Eric A. Suess is Chair and Professor of Statistics and Biostatistics and Bruce E. Trumbo is Professor Emeritus of Statistics and Mathematics, both at California State University, East Bay. Professor Suess is experienced in applications of Bayesian methods and Gibbs sampling to epidemiology. Professor Trumbo is a fellow of the American Statistical Association and the Institute of Mathematical Statistics, and he is a recipient of the ASA Founders Award and the IMS Carver Medallion.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Mathematical statistics.
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Statistical Theory and Methods.
Topical term or geographic name as entry element Statistics and Computing/Statistics Programs.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Trumbo, Bruce E.
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 9780387402734
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-0-387-68765-0
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
2014-04-08AUM Main Library2014-04-08 2014-04-08 E-Book   AUM Main Library519.5