Matlab多元回归regress实例

1、实用标准文案问题：y=7613.51 7850.91 8381.86 9142.81 10813.6 8631.43 8124.949429.79 10230.81 10163.61 9737.56 8561.06 7781.82 7110.97;x1=7666 7704 8148 8571 8679 7704 6471 5870 5289 3815 3335 29272758 2591;x2=16.22 16.85 17.93 17.28 17.23 17 19 18.22 16.3 13.37 11.62 10.369.83 9.25 回归成 y=ax1A2+bxM2+cx1+dx2+ex

2、1*x2+f(二次曲线)regress 解法：y=7613.517850.918381.869142.8110813.6 8631.43 8124.949429.79 10230.81 10163.61 9737.56 8561.06 7781.82 7110.97'x1=7666 7704 8148 8571 8679 7704 6471 5870 5289 3815 3335 29272758 2591'x2=16.22 16.85 17.93 17.28 17.23 17 19 18.22 16.3 13.37 11.62 10.369.83 9.25'X=o n

3、es(size(y) x1.A2 x2.A2 x1 x2 x1.*x2;b,bint,r,rint,stats = regress(y,X);format longb%b为对应的参数 b(1)为f, b(2)为a, b(3)为b, b为c, b为d , b(5) 为e%b =1.0e+004 *% -1.353935450267797% 0.000000089381408% -0.005811190715468% -0.000605427789545% 0.479983626458520% -0.000037869040292bint% 为 b 的95% 置信区间%bint = 1.0e+00

4、4 *% -2.621944842897243-0.085926057638351% 0.0000000342537530.000000144509063% -0.0275888316625450.015966450231609% -0.0013094938825460.000098638303455% 0.1195646935539060.840402559363135% -0.0001059543363410.000030216255756stats%stats 的第三个参数为F检验的P值，p值很小实用标准文案效P<0.001, 说明拟合模型有%stats = 1.0e+005 *0

5、.000000043344434%0.000008444011951 0.000086828553270scatter3(x1,x2,y,'filled')% 以下绘图查看拟合效果hold onx1fit = min(x1):100:max(x1);x2fit = min(x2):1:max(x2);X1FIT,X2FIT = meshgrid(x1fit,x2fit);实用标准文案YFIT=b(1)+b(2)*X 1F IT.T+b (3) *X2FIT.A2+b *X1F IT+b (5)*X2FIT+b (6)*X 1FIT.*X2FIT;mesh(X1FIT,X2FIT,YFIT)mesh(X1FIT,X2FIT,YFIT)vi