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Jingdong book

回归分析:因变量统计模型

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回归分析:因变量统计模型

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《回归分析:因变量统计模型》分为基本原理;问题及其补救的方法;回归的其他用途三篇, 主要内容包括: 均值分析: 基础知识复习和线性模型导言;简单线性回归分析: 单自变量线性回归等。
Catalogue

上篇 基本原理

1 均值分析:基础知识复习和线性模型导言

1.1 导言

1.2 抽样分布

辑本均值的抽样分南杰差的抽样分布 两个方差之比的抽群分布 各种分布之间的关系

1.3 单总体均值推论

用均值的抽样分布进行推论 用线性模型推论 假设检验

1.4 用独立样本推论双均值

用抽样分布进行推论 用线性模型进行双样本均值的推论

1.5 推论多个均值

重新参数化模型

1.6 小结

1.7 习题

2 简单线性回归分析:单自变量线性回归

2.1 导论

2.2 线性回归模型

2.3 推论参数□和口

估计参数□和□用抽样分布推论□用线性模型推论□

2.4 推论因变量

2.5 相关和决定系数

2.6 通过原点的回归

用抽样分布进行过原点的回归 甩线性摸性进行通过的回归

2.7 有关简单线性回归模型的假定

2.8 回归的使用与误用

2.9 反测

2.10 小结

2.11 习题

3 多元线性回归

3.1 导论

3.2 多元线性回归模型

3.3 系数估计

3.4 解释偏回归系数

用残差估计偏系数

3.5 推论参数

计算假设的ss 假设检验 普遍使用的检验 “模型”的检验 单个系数检验

同时推 用残差傲系数检验

3.6 检验广义线性假设(选读)

3.7 多元回归因变量推论

3.8 相关和决定系数

多重相关偏相关

3.9 求得结果

3.10 小结和前瞻

回归的使用和误用 数据问题模型网题

3.11 习题

中篇问题及其补救的方法

4 观察问题

4.1 导论

第一部分 异常值

4.2 异常值和影响值

基于残差的统计量 测量杠杆效应的统计量 测量因变量估计值影响的统计量

使用统计量DFBETAS杠杆效应图 测影响系数估计值精度的

统计量 评论 补救方法

第二部分 违反假定

4.3 不等方差

一般公式基于关系的权

4.4 稳健估计

4.5 相关误差

自回归模型 自相美诊颤法补救方法备择估计法

摸型修改

4.6 小结

4.7 习题

5多重共线性

5.1 导论

5.2 多重共线性效应

5.3 诊断多重共线性

方差膨胀因子方差比例 主成分

5.4 补救方法

变量再定义法 基于变量知识的方法 基于统计分折的方法 主或分回归

有偏估计 岭回归 不完全主成分回归

5.5 小结

5.6 习题

6 模型存在的问题

6.1 导论

6.2 设定误差

6.3 缺乏拟合检验

评论

6.4 过度设置:变量太多

6.5 变量选择法

子集的大小 统计量其他的选择法

6.6 变量选择的信度

交叉验证再抽样法

6.7 变量选择的效用

6.8 变量选择和影响值

评语

6.9 小结

6.10 习题

下篇 回归的其他用途

7 曲线拟合

7.1 导论

7.2 单自变量多项式模型

交互分析

7.3 节点已知的分段多项式

分段直线分段多项式

7.4 多个变量的多项式回归:响应面

7.5 无模型曲线拟合

移动平均数散点修匀法

7.6 小结

7.7 习题

8 非线性模型导论

8.1 导论

8.2 本质线性模型

乘法模型

8.3 本质非线性模型

成长模型

8.4 小结

8.5 习题

9 指示变量

9.1 导论

9.2 虚拟变量模型

相关变量的线性函数的均值和方差

9.3 格频数不等

9.4 空格

9.5 既有虚拟变量也有连续变量的模型

9.6 一种特殊的用法:协方差分析

9.7 协方差分析中的异构斜率问题

9.8 小结

9.9 习题

10 定类园变量

10.1 导论

10.2 二值因变量

二分因变量线性模型

11.3 加权最小平方

10.4 简单概率比对数回归

10.5 多元概率比对数回归

10.6 对数线性模型

10.7 小结

10.8 习题

11 广义线性模型

11.1 导论

11.2 连接函数

概率比对数回归连接泊松回归连接

11.3 概率比对数模型

11.4 其他模型

11.5 小结

附录A 统计表

A.1 标准正态分布――表A.1(正态分布表)和表A.1a(统计方法中的p值和z值)

A.2 T分布――表A.2统计方法中的r值

A.3 X2分布――表A.3统计方法中的X2值

A.4 F分布――表A.3统计方法中的F值

A.5 杜宾?瓦特森检验临界值

附录B 矩阵简介

B.1 矩阵代数

B.2 解线性方程

附录C 估计法

C.1 最小平方估计

C.2 最大似然估计

参考文献

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Brand Jingdong book
Brand Origin China

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