Introducing Monte Carlo Methods with R (Paperback)

Christian P. Robert, George Casella

  • 出版商: Springer
  • 出版日期: 2009-12-10
  • 售價: $3,280
  • 貴賓價: 9.5$3,116
  • 語言: 英文
  • 頁數: 304
  • 裝訂: Paperback
  • ISBN: 1441915753
  • ISBN-13: 9781441915757
  • 相關分類: R 語言
  • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

基於模擬的計算技術現已成為統計學家工具箱中不可或缺的一部分。因此,為統計學家提供對這些方法的實際理解至關重要,而使用模擬來解決統計問題是發展直覺和技能的最佳方式。《使用R介紹蒙特卡羅方法》從程序員的角度介紹了統計模擬中使用的主要工具,解釋了每種模擬技術的R實現,並提供輸出以便更好地理解和比較。雖然本書涵蓋了模擬方法的全面內容,但與Robert和Casella(2004)相比,這些方法的理論證明已大大減少。同樣,本書不涵蓋探索性較強且不太穩定的解決方案。

本書不需要對R編程語言或蒙特卡羅方法有預備知識,也不需要高深的數學背景。雖然許多示例是在貝葉斯框架下設置的,但不需要對貝葉斯統計學有高級專業知識。本書涵蓋了基本的隨機生成算法、蒙特卡羅積分和優化的技術、收斂診斷、馬爾可夫鏈蒙特卡羅方法,包括Metropolis-Hastings和Gibbs算法,以及自適應算法。所有章節都包含練習題,所有的R程序都可以作為一個名為mcsm的R包使用。本書適用於對模擬方法有實際興趣但沒有先前經驗的任何人。它旨在對統計學、信號處理、通信工程、控制理論、計量經濟學、金融等領域的學生和從業人員有所幫助。程式編寫部分逐步介紹,以便讓任何讀者都能理解。