Introduction to Scientific Programming and Simulation Using R, 2/e (Hardcover)

Owen Jones, Robert Maillardet, Andrew Robinson

Introduction to Scientific Programming and Simulation Using R, 2/e (Hardcover)
  • 出版商: CRC
  • 出版日期: 2014-06-12
  • 售價: $3,720
  • 貴賓價: 9.5 折 $3,534
  • 語言: 英文
  • 頁數: 606
  • 裝訂: Hardcover
  • ISBN: 1466569999
  • ISBN-13: 9781466569997
  • 相關分類: R 語言、數值分析 Numerical-analysis、程式語言

    • 海外代購書籍(需單獨結帳)

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商品描述

Learn How to Program Stochastic Models

 

Highly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data.

 

The book’s four parts teach:

 

 

  • Core knowledge of R and programming concepts
  • How to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisation
  • Essentials of probability, random variables, and expectation required to understand simulation
  • Stochastic modelling and simulation, including random number generation and Monte Carlo integration

 

In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size.

 

Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables.

 

Building readers’ statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.

商品描述(中文翻譯)

學習如何編程隨機模型

強烈推薦，《Introduction to Scientific Programming and Simulation Using R》第一版是一本暢銷書，被譽為一本優秀且易於閱讀的入門書，內容豐富，並提供大量的例子和練習題。第二版繼續以清晰、實用和全面的方式介紹科學編程和隨機建模。讀者通過實驗提供的R代碼和數據來學習編程。

本書分為四個部分教授以下內容：

1. R和編程概念的核心知識
2. 從數值角度思考數學，包括這些概念在根查找、數值積分和優化中的應用
3. 理解模擬所需的概率、隨機變量和期望的基礎知識
4. 隨機建模和模擬，包括隨機數生成和蒙特卡羅積分

在一個新的章節中，作者介紹了解決一階常微分方程組（ODEs）的Euler、中點和四階龍格-庫塔（RK4）方法。他們通過實驗比較了不同方法的數值效率，並展示了如何通過使用自適應步長來改進RK4方法。

另一個新章節專注於離散和連續時間馬可夫鏈。它描述了轉移和速率矩陣、狀態的分類、極限行為、科爾莫哥洛夫正向和反向方程、有限吸收鏈和預期達到時間。它還介紹了模擬離散和連續時間鏈的方法，以及定義狀態空間的技巧，包括合併狀態和輔助變量。

《Introduction to Scientific Programming and Simulation Using R, Second Edition》通過建立讀者的統計直覺，展示了如何將算法轉化為代碼。它適用於那些想要創建工具而不僅僅是使用工具的人。代碼和數據可從CRAN下載。

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