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逐步回归
- 程序采用可视化界面，对概率统计中的逐步回顾算法，用户可以在界面上输入变量个数，试验次数，对各种情况均可计算，最后输出回归方程。还可以从文件中载入数据，保存数据。-procedures used visualization interface to statistical probability of gradually recalled algorithm, users can interface the number of input variables, the number of all
统计回归3.00版
- 统计回归软件3.00版， 应用本程序，可以方便快速的建立多元一次回归方程，如气象上统计预报方程的建立等。-statistical regression software version 3.00, the application procedures, to facilitate the rapid establishment of a multiple regression equation, such as meteorological forecasting equation statis
caculation1
- 主要介绍回归分析，即确定自变量与因变量之间的定量关系，所建立的定量表达式称为回归方程；对自变量与因变量之间的关系进行检验； -introduced regression analysis, identify variables and dependent variables between the quantitative relationship, the establishment of quantitative formula known as the regression equat
caculation2
- 主要介绍逐步回归的方法，并介绍如何利用逐步回归建立最佳线性回归方程。-introduced stepwise regression method, and how to use stepwise regression to establish the best linear regression equation.
shuxuejianmo_5.rar
- （回归分析） 考察温度x对产量y的影响，测得下列10组数据： 求y关于x的线性回归方程，检验回归效果是否显著，并预测x=42℃时产量的估值及预测区间（置信度95 ） ,(Regression analysis) x on the output of the temperature study of the impact of y, measured the following 10 sets of data: for y on x of the linear regression
backstep
- 实现多元线性回归方程自变量的选择及系数的求解，获得显著性拟合方程-The realization of multiple linear regression equations to solve significant
matlabtext2
- 考察温度x对产量y的影响，测得下列10组数据：求y关于x的线性回归方程，检验回归效果是否显著，并预测x=42℃时产量的估值及预测区间（置信度95 ） 示例包含在内-X on the output of the temperature study of the impact of y, measured the following 10 sets of data: for y on x of the linear regression equation to test whether the
exer5
- 回归分析 考察温度x对产量y的影响 测得下列10组数据 求y关于x的线性回归方程 检验回归效果是否显著 并预测x=42℃时产量的估值及预测区间-Regression analysis, study the temperature on the yield y of x measured by the following 10 sets of data demand y on x, the linear regression equation of the regression effect is
Timeseriers
- 对加拿大山猫捕获数量进行时间序列分析，建立自回归方程，并对未来的捕获数量进行了预测-To capture the number of Canadian lynx time-series analysis, since the regression equation, and the future was predicted to capture the number of
WindowsApplicationHangshu
- 这是用C#写的有关实现多维回归方程的程序，是多元一次的回归方程，如果是多次多元也可以转化为多元一次这一类来实现～-It is written in C# for the realization of multi-dimensional regression equation procedure is a multiple regression equation, if it is repeated multiple can be turned into this kind of first to
ZPHG.RAR
- 一个由VB6.0编写的逐步回归源程序，可解多元线性回归方程。-Prepared by a stepwise regression VB6.0 source code, multiple linear regression equation solvable.
Linear-regression-equation
- 一元线性回归方程， 求线性回归方程：Y = a + bx 的回归系数a和b. 用的是最小二乘法推导的结果。网上搜索最小二乘法原理，配合这个源代码学习还是不错的。本代码是网上搜来的，发现自学用不错，特上传分享。-Linear regression equation, find the linear regression equation: Y = a+ bx the regression coefficients a and b. derived using a least squares res
stepwise
- 逐步回归的基本思想是将变量逐个引入模型，每引入一个解释变量后都要进行F检验，并对已经选入的解释变量逐个进行t检验，当原来引入的解释变量由于后面解释变量的引入变得不再显著时，则将其删除。以确保每次引入新的变量之前回归方程中只包含显著性变量。这是一个反复的过程，直到既没有显著的解释变量选入回归方程，也没有不显著的解释变量从回归方程中剔除为止。以保证最后所得到的解释变量集是最优的。(In statistics, stepwise regression is a method of fitting re
第十章
- 数学建模第十章线性回归方程，简单易懂，适合数学建模学生(Mathematical modeling, the tenth chapter, linear regression equation)
linear_regression
- 线性回归是利用称为线性回归方程的最小二乘函数对一个或多个自变量和因变量之间关系进行建模的一种回归分析(Linear regression is a regression analysis based on the least squares function of linear regression equation, which is used to model the relationship between one or more independent variables and dep
逐步回归
- matlab简易逐步回归，内含2、3、4、5、6、8、10个因子回归时代码，对多因子进行排列组合，按照因子数进行回归，寻找最佳因子个数的回归方程。(Matlab simple step by step regression, containing 2, 3, 4, 5, 6, 8, 10 factors regression code, arranged on the multi-factor combination, regression in accordance with the numb
PCA equation
- 主成分分析法求得主成分回归方程，从而达到降维目的。(Principal component analysis method for obtaining the regression equation of principal components)
rqpd_0.6
- 对数进行分位数回归分析，求得分位数回归方程参数。(The quantile regression analysis is performed on the logarithm to obtain the number of regression equations for the score.)
Maple化学反应速率方程参数拟合与回归分析
- Maple化学反应速率方程参数拟合与回归分析(Parameter fitting and regression analysis of Maple chemical reaction rate equation)
best_linear_regression_equation
- 病人有四个指标：X1：凝血值；X2：预后指数（与年龄相关）；X3：酶化验值；X4肝功能化验值。54位肝病人术前数据与术后生存时间如表所示.病人生存时间的Box-Cox变换变量Z与X1，X2，X3，X4的线性回归模型是合理的，程序实现了如何选择最优回归方程。(Patients have four indexes: X1: coagulation value; x2: prognosis index (related to age); X3: enzyme test value; X4 liver