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PCA and PLS aims:to get some
insight into the bilinear factor models Principal Component Analysis
(PCA) and Partial Least Squares (PLS) regression, focusing on the
mathematics and numerical aspects rather than how s and why s of
data analysis
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Numerical Computing with MATLAB (by Cleve Moler) is a textbook for an introductory course
in numerical methods, Matlab, and technical computing. The emphasis is on in-
formed use of mathematical software. We want you learn enough about the mathe-
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Toolbox for Numerical Computing with MATLAB (by Cleve Moler).
Numerical Computing with MATLAB (by Cleve Moler) is a textbook for an introductory course
in numerical methods, Matlab, and technical computing. The emphasis is on in-
formed u
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根据最小二乘法由一组点拟合一条直线-by the least squares method based on a group fitting a linear point
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The toolbox solves a variety of approximate modeling problems for linear static models. The model can be parameterized in kernel, image, or input/output form and the approximation criterion, called misfit, is a weighted norm between the given data an
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灰色预测模型称为CM模型,G为grey的第一个字母,M为model的第一个字母。GM(1,1)表示一阶的,一个变量的微分方程型预测模型。GM(1,1)是一阶单序列的线性动态模型,主要用于时间序列预测。 一、GM(1,1)建模 设有数列 共有 个观察值 对 作累加生成,得到新的数列 ,其元素 (5-1) 有: 对数列 ,可建立预测模型的白化形式方程, (5-2) 式中: ——为待估计参数。分别称为发展灰数和内生控制灰数。设 为待估计参数向量 则 按最小二乘法求解, 有: (5-3) 式中: (5-
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This directory contains utility for implementing generic Reqursive Least Squares (RLS) algorithm. The example shows how one can use the utility to estamate the parameters of a simple linear discrete time system.
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数据预测算法,主要是一元n次方程的回归预测实现。* 预测分析--本算法只适用于有明显线性趋势的数据 * 默认为一元二次曲线方程法 * * 本程序主要涉及有两个算法 * 1.用最小二乘原理找到线性方程组的系数和常数。 * 2.解线性方程组 * 本程序在解线性方程组中,由于考虑到收敛性问题未采用迭代法,而是采用Gauss-Jordan消去法来解决。-data prediction algorithm is mainly one yuan n equation forecast to achieve
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pls算法工具箱。偏最小二乘回归≈多元线性回归分析+典型相关分析+主成分分析
,pls algorithm toolbox. Partial least-squares regression ≈ multiple linear regression analysis, canonical correlation analysis++ Principal component analysis
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基于核函数的偏最小二乘算法,先对原矩阵进行核函数非线性变化,再用非线性迭代求解-Kernel-based partial least-squares algorithm, first the original non-linear function of changes in the nuclear matrix, and then non-linear iterative solution
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北航数值分析大作业三,功能为用Newdon法求解非线性方程组,Gauss法求解线性方程组,求矩阵的逆,二元二次插值,按最小二乘原则进行二元拟合并自动寻找最小阶数。-Northern analysis of large numerical operations three functions with Newdon method for solving nonlinear equations, Gauss method for solving linear equations, find the
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系统 辨识文件夹内是产生高斯白噪声,m序列和最小二乘法的一次完成算法,递推算法,限定记忆法的程序。系统仿真文件夹内是对系统线性和非线性的建模和仿真程序。-System folder on system identification is to generate Gaussian white noise, m sequence and a complete least-squares method algorithm, recursive algorithm, limited memory met
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最小二乘法多元线性回归的matlab实现-Least squares linear regression of the matlab implementation
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线性回归算法 用matlab实现多元线性回归 用最小二次方法来实现-REGRESS Multiple linear regression using least squares
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最小二乘法一般是用来拟合直线和一些线性数据的,就是用一条直线来尽可能的表达若干的点的趋势,当然直线穿过所有的点是最好的,但往往有误差存在,所以拟合出的直线要求误差最小.设这些点为(x1,y1),(x2,y2)....(xn,yn).拟合直线为y=kx+b.-Ordinary least squares method is used to fit a straight line and a number of linear data, that is, as far as possible wit
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偏最小二乘法PLS广泛应用于很多领域。这个程序包提供了一个函数,使用非线性迭代偏最小二乘法NIPALS算法,实现PLS回归。同时包含NIPALS算法的教程-PLS PLS is widely used in many areas. This package provides a function, use of non-linear iterative partial least squares algorithm NIPALS achieve PLS regression. NIPALS al
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数值分析中的线性代数方程组的数值解法中最小二乘算法的c实现。-Numerical analysis numerical solution of linear algebraic equations in the least squares algorithm c.
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最小二乘法原理及其MATLAB实现 线性拟合 多项式拟合 非线性拟合程序-Principle and MATLAB least squares linear fitting polynomial fitting nonlinear fitting procedure
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这是龚纯《精通MATLAB最优化计算》随书源码(M文件)。基于MATLAB优化工具箱,代码包含的内容有:牛顿法等无约束一维极值问题、单纯形搜索法等无约束多维极值问题、Rosen梯度投影法等约束优化问题、L-M法等非线性最小二乘优化问题、线性规划、整数规划、二次规划、粒子群优化、遗传算法。-This is pure Gong " Mastering MATLAB optimization calculations," with the book source (M file)
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最小二乘支持向量机,用于多元非线性回归分析,非线性拟合与预测-Least squares support vector machine for multi-linear regression analysis, nonlinear fitting and prediction
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