%多元线性回归求解

clear

clc

x=[120731808012512581.190

133.02731808012512581.190

129.63731808012512581.190

158.77731808012512581.190

145.32731808012512581.190

12078.5961808012512581.190

12075.451808012512581.190

12090.4871808012512581.190

12083.8481808012512581.190

12073231.398012512581.190

12073198.488012512581.190

12073212.648012512581.190

12073190.558012512581.190

1207318075.85712512581.190

1207318065.95812512581.190

1207318087.25812512581.190

1207318097.82412512581.190

1207318080150.7112581.190

1207318080141.5812581.190

1207318080132.3712581.190

1207318080156.9312581.190

1207318080125138.8881.190

1207318080125131.2181.190

1207318080125141.7181.190

1207318080125149.2981.190

120731808012512560.58290

120731808012512570.96290

120731808012512564.85490

120731808012512575.52990

120731808012512581.1104.84

120731808012512581.1111.22

120731808012512581.198.092

120731808012512581.1120.44

];

y=[164.78140.87-144.25119.09135.44157.69

165.81140.13-145.14118.63135.37160.76

165.51140.25-144.92118.7135.33159.98

167.93138.71-146.91117.72135.41166.81

166.79139.45-145.92118.13135.41163.64

164.94141.5-143.84118.43136.72157.22

164.8141.13-144.07118.82136.02157.5

165.59143.03-143.16117.24139.66156.59

165.21142.28-143.49117.96137.98156.96

167.43140.82-152.26129.58132.04153.6

165.71140.82-147.08122.85134.21156.23

166.45140.82-149.33125.75133.28155.09

165.23140.85-145.82121.16134.75156.77

164.23140.73-144.18119.12135.57157.2

163.04140.34-144.03119.31135.97156.31

165.54141.1-144.32118.84135.06158.26

166.88141.4-144.34118.67134.67159.28

164.07143.03-140.97118.75133.75158.83

164.27142.29-142.15118.85134.27158.37

164.57141.44-143.3119134.88158.01

163.89143.61-140.25118.64133.28159.12

166.35139.29-144.2119.1136.33157.59

165.54140.14-144.19119.09135.81157.67

166.75138.95-144.17119.15136.55157.59

167.69138.07-144.14119.19137.11157.65

162.21141.21-144.13116.03135.5154.26

163.54141-144.16117.56135.44155.93

162.7141.14-144.21116.74135.4154.88

164.06140.94-144.18118.24135.4156.68

164.66142.27-147.2120.21135.28157.65

164.7142.94-148.45120.68135.16157.63

164.67141.56-145.88119.68135.29157.61

164.69143.84-150.34121.34135.12157.64

];

[m,n]=size(x);

X=[ones(m,1) x];

[m1,n1]=size(X);

[m2,n2]=size(y);

for i=1:n2

%b为参数，bint回归系数的区间估计，r为残差，

%rint为置信区间，stats用于回归模型检验

[b(:,i),bint,r,rint,stats(i,:)]=regress(y(:,i),X);

[mm,nn]=size(b);

for jj=1:m1

temp=0;

for ii=1:mm

yy(jj,i)=temp+b(ii,i)*X(jj,ii);