matlab多元非线性回归及显着性分析(实例).doc

matlab多元非线性回归及显著性分析给各位高手：小弟有一些数据需要回归分析（非线性）及显著性检验（回归模型，次要项，误差及失拟项纯误差，F值和P值），求大侠帮助，给出程序，不胜感激。模型： DATA=. %DATA前三列是影响因子，第四列为响应值 2 130 75 48.61; 2 110 75 56.43; 2 130 45 61.32; 2 110 45 65.28; 1 110 45 55.80; 1 130 75 45.65; 1 110 75 50.91; 1 130 45 67.94; 1.5 120 60 74.15; 1.5 120 60 71.28; 1.5 120 60 77.95; 1.5 120 60 74.16; 1.5 120 60 75.20; 1.5 120 85 35.65; 1.5 140 60 48.66; 1.5 120 30 74.10; 1.5 100 60 62.30; 0.5 120 60 66.00; 2.5 120 60 75.10;回归分析过程：（1）MATLAB编程步骤1：首先为非线性回归函数编程，程序存盘为user_function.mfunction y=user_function(beta,x)b0 = beta(1);b1 = beta(2);b2 = beta(3);b3 = beta(4);x0 = x(:,1);x1 = x(:,2);x2 = x(:,3);x3 = x(:,4);y=b0*x0+b1*x1.2+b2*x2.2+b3*x3.2;（2）MATLAB编程步骤2：编写非线性回归主程序，程序运行时调用函数user_functionx=1 2 130 75 48.61; 1 2 110 75 56.43; 1 2 130 45 61.32; 1 2 110 45 65.28; 1 1 110 45 55.80; 1 1 130 75 45.65; 1 1 110 75 50.91; 1 1 130 45 67.94; 1 1.5 120 60 74.15; 1 1.5 120 60 71.28; 1 1.5 120 60 77.95; 1 1.5 120 60 74.16; 1 1.5 120 60 75.20; 1 1.5 120 85 35.65; 1 1.5 140 60 48.66; 1 1.5 120 30 74.10; 1 1.5 100 60 62.30; 1 0.5 120 60 66.00; 1 2.5 120 60 75.10; %第1列全是1，第6列是指标变量，其余列是自变量xx=x(:,1:5);yy=x(:,5);%指定响应变量yy和自变量xxbeta0=0.5 0.4 0.7 0.5;%设置初始回归系数（如何确定初值？）beta_fit,residual = nlinfit(xx,yy,user_function,beta0)%非线性回归结果beta_fit = 91.3757 1.2712 -0.0009 -0.0049residual = -4.2935 -1.0248 -9.2044 -9.7957-15.4620 -3.4398 -2.7311 1.2293 11.1889 8.3189 14.9889 11.1989 12.2389 -9.5678 -9.3704