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# 向量的应用

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2.1 最小二乘法的定义································· (2) 2.2 最小二乘法的统计学原理 ···························· (2) 第 3 章 最小二乘法的应用
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3.1 曲线拟合 ······································· (7) 3.1.1 一元线性拟合································· (7) 3.1.2 多元线性拟合································· (7) 3.1.3 多项式拟合
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3.1.4 非线性最小二乘法拟合

3.1.5 可化为线性拟合的非线性拟合

3.2 加权最小二乘法 ···································· (7) 3.2.1 加权最小二乘法定义
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3.2.2 加权最小二乘法原理 ···························· (7) 第 4 章 应用最小二乘法解决的实际问题 ······················ (7) 4.1 一元线性拟合实例 ······························· (8) 4.2 多项式拟合实例································· (8) 4.3 非线性拟合 ······································ 4.4 可化为线性拟合的非线性拟合
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5.1.1 一元线性拟合的程序设计原理 5.1.2 多元线性拟合的程序设计原理

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5.2 MATLAB 对最小二乘法的实现 ·························· 5.2.1 用 Matlab 实现曲线拟合
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5.2.2 实例 ·········································

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