Numerical Methods of Statistics, 2/e (Paperback)

This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. Each chapter contains exercises that range from simple questions to research problems. Most of the examples are accompanied by demonstration and source code available in from the author's Web site. New in this second edition are demonstrations coded in R, as well as new sections on linear programming and the Nelder-Mead search algorithm.

這本書解釋了計算機軟體如何設計以執行複雜的統計分析任務。對於統計學家來說，它探討了統計方法背後的具體計算問題。對於數學家和計算機科學家來說，它則關注數學工具在統計問題中的應用。本書的前半部分提供了一個基礎的數值分析背景，強調對統計學家重要的問題。接下來的幾章涵蓋了各種統計工具，如最大概似法和非線性回歸。作者還介紹了數值工具的應用；數值積分和隨機數生成以統一的方式解釋，反映了蒙特卡羅方法的互補觀點。每章都包含從簡單問題到研究問題的練習題。大多數示例都附有作者網站上提供的演示和源代碼。第二版新增了用R編寫的演示，以及關於線性規劃和Nelder-Mead搜索算法的新章節。