那位好心人用MATLAB给我计算一下几组数据的一次线性回归系数

那位好心人用MATLAB给我计算一下几组数据的一次线性回归系数
第一组(1,1.283)(0.6667,1.476)(0.5,1.598)(0.3333,1.770)(0.25,1.908)
第二组(1,0.8255)(0.6667,1.0277)(0.5,1.1745)(0.3333,1.3912)(0.25,1.5601)
第三组(1,0.943)(0.6667,1.059)(0.5,1.152)(0.3333,1.266)(0.25,1.364)
第四组(1,0.6642)(0.6667,0.8012)(0.5,0.9098)(0.3333,1.0562)(0.25,1.1773)
第五组(1,0.550)(0.6667,0.642)(0.5,0.710)(0.3333,0.795)(0.25,0.864)
第六组(1,0.4383)(0.6667,1.470.53446)(0.5,0.6076)(0.3333,0.7052)(0.25,0.7823)
第七组(1,0.477)(0.6667,0.528)(0.5,0.592)(0.3333,0.648)(0.25,0.708)
第八组(1,0.39)(0.6667,0.4524)(0.5,0.5186)(0.3333,0.5867)(0.25,0.6519))
能采取这种形式
x=(1 2/3 1/2 1/3 1/4)
y1=(1.283 1.476 1.598 1.770 1.908)
y2=(0.8255 1.0277 1.1745 1.3912 1.5601)
y3=(0.943 1.059 1.152 1.266 1.364)
y4=(0.6642 0.8012 0.9098 1.0562 1.1773)
y5=(0.550 0.642 0.710 0.795 0.864)
y6=(0.4383 0.5344 0.6076 0.7052 0.7823)
y7=(0.477 0.528 0.592 0.648 0.708)
y8=(0.390 0.4524 0.5186 0.5867 0.6519)
问题中第6组数据输错了

是这样吗?
clc;clear;
x=[1 2/3 1/2 1/3 1/4]
y1=[1.283 1.476 1.598 1.770 1.908];
y2=[0.8255 1.0277 1.1745 1.3912 1.5601];
y3=[0.943 1.059 1.152 1.266 1.364];
y4=[0.6642 0.8012 0.9098 1.0562 1.1773];
y5=[0.550 0.642 0.710 0.795 0.864];
y6=[0.4383 0.5344 0.6076 0.7052 0.7823];
y7=[0.477 0.528 0.592 0.648 0.708];
y8=[0.390 0.4524 0.5186 0.5867 0.6519] ;
Y=[y1;y2;y3;y4;y5;y6;y7;y8]
plot(x,Y,'o-')
for k=1:8
p1(k,:)=polyfit(x,Y(k,:),1);%一次回归系数
p2(k,:)=polyfit(x,Y(k,:),2);%二次回归系数
end
p1,p2
xx=min(x):0.05:max(x);
for m=1:8
Y1(m,:)=polyval(p1(m,:),xx);
Y2(m,:)=polyval(p2(m,:),xx);
end
figure
plot(x,Y,'o',xx,Y1)
figure
plot(x,Y,'o',xx,Y2)
运行结果：
x = 1.0000 0.6667 0.5000 0.3333 0.2500
Y =
1.2830 1.4760 1.5980 1.7700 1.9080
0.8255 1.0277 1.1745 1.3912 1.5601
0.9430 1.0590 1.1520 1.2660 1.3640
0.6642 0.8012 0.9098 1.0562 1.1773
0.5500 0.6420 0.7100 0.7950 0.8640
0.4383 0.5344 0.6076 0.7052 0.7823
0.4770 0.5280 0.5920 0.6480 0.7080
0.3900 0.4524 0.5186 0.5867 0.6519
p1 =
-0.8051 2.0498
-0.9473 1.7168
-0.5434 1.4557
-0.6614 1.2855
-0.4065 0.9358
-0.4452 0.8584
-0.2985 0.7548
-0.3385 0.7061
p2 =
0.6792 -1.6581 2.2652
0.9742 -2.1708 2.0257
0.5261 -1.2041 1.6225
0.6907 -1.5288 1.5045
0.3568 -0.8546 1.0489
0.4309 -0.9863 0.9951
0.3386 -0.7238 0.8622
0.3719 -0.8055 0.8240
还是二次拟合比较好.