Appendix E 概念索引

• CRAN: Contributed packages and CRAN
• Kolmogorov-Smirnov 检验。: Examining the distribution of a set of data
• QR 分解: Least squares fitting and the QR decomposition
• Shapiro-Wilk 检验: Examining the distribution of a set of data
• t 检验: One- and two-sample tests
• Wilcoxon 检验: One- and two-sample tests
• 二元操作符: Defining new binary operators
• 从文件中读取数据: Reading data from files
• 作用域: Scope
• 公式: Formulae for statistical models
• 分位比较图: Examining the distribution of a set of data
• 列表: Lists
• 列表连接: Concatenating lists
• 删除对象: Data permanency and removing objects
• 制表: Frequency tables from factors
• 动态图形: Dynamic graphics
• 包: Packages
• 包: R and statistics
• 单样本和双样本检验: One- and two-sample tests
• 参数命名: Named arguments and defaults
• 向量: Simple manipulations numbers and vectors
• 命名空间: Namespaces
• 因子: Contrasts
• 因子: Factors
• 图形参数: The par() function
• 图形设备驱动: Device drivers
• 奇异值分解: Singular value decomposition and determinants
• 字符向量: Character vectors
• 定制环境: Customizing the environment
• 定向输入和输出: Executing commands from or diverting output to a file
• 密度估计: Examining the distribution of a set of data
• 对照: Contrasts
• 对象: Objects
• 局部近似回归: Some non-standard models
• 属性: Objects
• 工作空间: Data permanency and removing objects
• 广义线性模型: Generalized linear models
• 循环使用原则: Vector arithmetic
• 循环使用原则: The recycling rule
• 循环和条件控制: Loops and conditional execution
• 成组表达式: Grouped expressions
• 控制语句: Control statements
• 搜索路径: Managing the search path
• 数据框: Data frames
• 数组: Arrays
• 数组的外积: The outer product of two arrays
• 数组的广义转置: Generalized transpose of an array
• 数组索引: Array indexing
• 方差分析: Analysis of variance and model comparison
• 族: Families
• 更新拟合模型: Updating fitted models
• 最大似然法: Maximum likelihood
• 最小二乘法拟合: Least squares fitting and the QR decomposition
• 有序因子: Factors
• 有序因子: Contrasts
• 树型模型: Some non-standard models
• 概率分布: Probability distributions
• 正则序列: Generating regular sequences
• 泛型函数: Object orientation
• 混合模型: Some non-standard models
• 特征值和特征向量: Eigenvalues and eigenvectors
• 盒状图: One- and two-sample tests
• 矩阵: Arrays
• 矩阵相乘: Multiplication
• 稳健回归: Some non-standard models
• 算术函数和运算符: Vector arithmetic
• 类: The class of an object
• 类: Object orientation
• 索引向量: Index vectors
• 累加模型: Some non-standard models
• 线性方程: Linear equations and inversion
• 线性模型: Linear models
• 经验累积分布函数: Examining the distribution of a set of data
• 统计模型: Statistical models in R
• 编写函数: Writing your own functions
• 缺省值: Missing values
• 行列式: Singular value decomposition and determinants
• 访问内置数据: Accessing builtin datasets
• 赋值: Vectors and assignment
• 非线性最小二乘法: Nonlinear least squares and maximum likelihood models
• 面向对象: Object orientation
• 默认值: Named arguments and defaults