商品描述
Taking advantage of both user-developed code and specialized functions, this second edition of An R Companion to Linear Statistical Models again targets two primary audiences: Those who are familiar with the introductory theory and applications of linear statistical models and who wish to learn how to use R in this area, or explore further ideas that might appear in this Companion; and those who are enrolled in an intermediate to advanced level course on linear statistical models for which R is the computational platform.
This Companion includes accessible introductions to writing R code as well as making use of functions through relevant examples. These examples cover methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. Also included in this edition is a new part containing chapters that revisit the one-factor fixed-effects model from alternative points of view, and provide introductions to applying R to nonstandard linear contrasts, one-factor random-effects and repeated-measures designs, weighted least squares, and modelling with binary response data.
Key Features
- Demonstrates how to create user-defined functions, and how to use pre-packaged functions from the Comprehensive R Archive Network (CRAN) as well as functions prepared specifically for this Companion.
- Has carefully documented accompanying R script files that follow along with the discussions in the book, and also contain additional exploratory code.
- Makes use of a relevant collection of examples to demonstrate both the statistical methods being discussed, as well as the R code used implement the methods.
- Provides detailed interpretations and explanations of graphical tools used, computed model parameter estimates, associated tests, and common "rules of thumb" used in interpreting graphs and computational output.
- Limits statistical and mathematical background theory to that which aids in following computational methods.
商品描述(中文翻譯)
利用用戶開發的程式碼和專門功能，本書第二版《An R Companion to Linear Statistical Models》再次針對兩個主要讀者群體：一是熟悉線性統計模型的入門理論和應用，並希望學習如何在這個領域使用 R，或探索本書中可能出現的進一步想法；二是參加中級到高級線性統計模型課程的學生，該課程以 R 作為計算平台。
本書附錄提供了易於理解的 R 程式碼撰寫介紹，以及通過相關範例使用函數的方式。這些範例涵蓋了用於線性回歸和設計實驗的方法，最多包含兩個固定效應因子，包括阻擋變數和協變數。本版還新增了一部分，包含重新從不同角度檢視單因子固定效應模型的章節，並介紹如何將 R 應用於非標準線性對比、單因子隨機效應和重複測量設計、加權最小二乘法，以及使用二元響應數據建模。
主要特點
- 演示如何創建用戶自定義函數，以及如何使用來自綜合 R 存檔網絡 (CRAN) 的預包裝函數，以及專門為本書準備的函數。
- 提供仔細記錄的 R 腳本文件，與書中的討論相輔相成，並包含額外的探索性程式碼。
- 利用相關範例集合來演示所討論的統計方法，以及用於實現這些方法的 R 程式碼。
- 提供詳細的圖形工具解釋和說明，包括計算的模型參數估計、相關測試，以及在解釋圖形和計算輸出時常用的「經驗法則」。
- 將統計和數學背景理論限制在有助於理解計算方法的範圍內。
作者簡介
Christopher Hay-Jahans is a professor of mathematics at the University of Alaska Southeast in Juneau, AK. He enjoys teaching all levels of mathematics and statistics and, more recently, he has been dabbling in mentoring undergraduate biomathematics research projects through annual IBA CURE Workshops.
作者簡介(中文翻譯)
克里斯多福·海-雅漢斯是阿拉斯加東南大學（University of Alaska Southeast）數學教授，位於阿拉斯加州朱諾市（Juneau, AK）。他喜歡教授各個級別的數學和統計學，最近，他也開始透過每年的 IBA CURE 工作坊指導本科生的生物數學研究項目。
