MATLAB拟合多元非线性函数?自变量x1=【101 98.4 98.8 98.5 98.6 98.2 98.8 99.2 99.5 100.6 101.9 101.5 102.7 102.4 102.8 103.1 102.9 103.3 103.5 103.6 104.4 105.1 104.6 104.9 104.9 105.4 105.3 105.5 106.4 106.5 106.2 106.1 105.5 104.2 104.1 1

MATLAB拟合多元非线性函数?自变量x1=【101 98.4 98.8 98.5 98.6 98.2 98.8 99.2 99.5 100.6 101.9 101.5 102.7 102.4 102.8 103.1 102.9 103.3 103.5 103.6 104.4 105.1 104.6 104.9 104.9 105.4 105.3 105.5 106.4 106.5 106.2 106.1 105.5 104.2 104.1 1
MATLAB拟合多元非线性函数?
自变量x1=【
101 98.4 98.8 98.5 98.6 98.2 98.8 99.2 99.5 100.6 101.9 101.5 102.7 102.4 102.8 103.1 102.9 103.3 103.5 103.6 104.4 105.1 104.6 104.9 104.9 105.4 105.3 105.5 106.4 106.5 106.2 106.1 105.5 104.2 104.1 104.5 103.2 103.6 103.4 103 102.2 101.8
】
x2=【
496135.31 506708.07 530626.71 540481.21 548263.51 568916.2 573102.85 576698.95 576698.95 586643.29 594604.72 610224.52 625609.29 636072.26 649947.46 656561.22 663351.37 673921.72 674051.48 687506.92 696471.5 699776.74 710339.03 725851.79 733884.83 736130.86 758130.88 757384.56 763409.22 780820.85 772923.65 780852.3 787406.2 816829.25 825493.94 851590.9 855898.89 867177.63 895600 889600 900000 925000 919100
】
因变量y=【
6.903106 7.225627 8.235698 8.568031 9.057412 10.11868 11.53129 9.041437 9.371831 10.11123 10.83773 11.08377 10.10374 10.33224 10.57647 9.668508 8.662745 7.931444 7.811012 7.725547 7.753376 8.71688 8.187911 8.159127 8.164803 8.515319 8.592566 8.616842 7.977995 7.960922 7.722894 7.343536 6.759 7.079082 6.683803 6.322855 6.596952 7.004311 6.512667 6.890974 6.786185 6.329737 5.968858
】
怎样用MATLAB拟合y关于x1和x2的非线性曲线呢?选的模型是y=a*x1+b*x2+c*x1.^2+d*x2.^2+e

MATLAB拟合多元非线性函数?自变量x1=【101 98.4 98.8 98.5 98.6 98.2 98.8 99.2 99.5 100.6 101.9 101.5 102.7 102.4 102.8 103.1 102.9 103.3 103.5 103.6 104.4 105.1 104.6 104.9 104.9 105.4 105.3 105.5 106.4 106.5 106.2 106.1 105.5 104.2 104.1 1
>> x1=[101 98.4 98.8 98.5 98.6 98.2 98.8 99.2 99.5 100.6 101.9 101.5 102.7 102.4 102.8 103.1 102.9 103.3 103.5 103.6 104.4 105.1 104.6 104.9 104.9 105.4 105.3 105.5 106.4 106.5 106.2 106.1 105.5 104.2 104.1 104.5 103.2 103.6 103.4 103 102.2 101.8
];
>> x2=[496135.31 506708.07 530626.71 540481.21 548263.51 568916.2 573102.85 576698.95 576698.95 586643.29 594604.72 610224.52 625609.29 636072.26 649947.46 656561.22 663351.37 673921.72 674051.48 687506.92 696471.5 699776.74 710339.03 725851.79 733884.83 736130.86 758130.88 757384.56 763409.22 780820.85 772923.65 780852.3 787406.2 816829.25 825493.94 851590.9 855898.89 867177.63 895600 889600 900000 925000 ];
>> x3=x1.^2;
>> x4=x2.^2;
>> y=[6.903106 7.225627 8.235698 8.568031 9.057412 10.11868 11.53129 9.041437 9.371831 10.11123 10.83773 11.08377 10.10374 10.33224 10.57647 9.668508 8.662745 7.931444 7.811012 7.725547 7.753376 8.71688 8.187911 8.159127 8.164803 8.515319 8.592566 8.616842 7.977995 7.960922 7.722894 7.343536 6.759 7.079082 6.683803 6.322855 6.596952 7.004311 6.512667 6.890974 6.786185 6.329737 ];
>> x=[ones(42,1),x1',x2',x3',x4'];
>> [b,bint,r,rint,stats]=regress(y',x)

> In regress at 78
b =
0
-0.1380
0.0001
-0.0014
-0.0000



e=b(1) a=b(2) b=b(3) c=b(4) d=b(5)

y=-0.1380*x1+0.0001*x2-0.0014*x1.^2