急求GM(1,N)的matlab程序！！！！

% GM(1,1)模型计算及检验、作图。文件名fungry1.m
function GM1=fungry1(x0) %输入原始数据x0
T=input('T=')
x1=zeros(1,length(x0));
B=zeros(length(x0)-1,2);
yn=zeros(length(x0)-1,1);
Hatx0=zeros(1,length(x0)-1,2);
Hatx00=zeros(1,length(x0));
Hatx1=zeros(1,length(x0)+T);
epsilon=zeros(length(x0),1);
omega=zeros(length(x0),1);
for i=1:length(x0)
for j=1:i
x1(i)=x1(i)+x0(j);
end
end
for i=1:length(x0)-1
B(i,1)=(-1/2)*(x1(i)+x1(i+1));
B(i,2)=1;
yn(i)=x0(i+1);
end
HatA=(inv(B'*B))*B'*yn;% GM(1,1)模型参数估计
a=HatA(1)
b=HatA(2)
for k=1:length(x0)+T
Hatx1(k)=(x0(1)-b/a)*exp(-a*(k-1))+b/a
end
Hatx0(1)=Hatx1(1);
for k=2:length(x0)+T
Hatx0(k)=Hatx1(k)-Hatx1(k-1) % 累减还原得到历史数据的模拟值
end
for i=1:length(x0) % 开始模型检验
epsilon(i)=x0(i)-Hatx0(i);
omega(i)=(epsilon(i)/x0(i))*100;
end
c=std(epsilon)/std(x0);p=0;
for i=1:length(x0)
if abs(epsilon(i)-mean(epsilon))<0.6745*std(x0)
p=p+1;
end
p=p/length(x0)
if p>0.95 & c<0.35
disp('The model is good,and the forecast is:');
disp(Hatx0(length(x0)+T))
elseif p>0.85 & c<0.5
disp('The model is eligibility,and the forecast is:');
disp(Hatx0(length(x0)+T))
elseif p>0.70 & c<0.65
disp('The model is not good,and the forecast is:');
disp(Hatx0(length(x0)+T))
else p<=0.70 & c>0.65
disp('The model is bad and try again')
end
for i=1:length(x0)
Hatx00(i)=Hatx0(i);
end
z=1:length(x0);
plot(z,x0,'-',z,Hatx00,':') %将原始数据和模拟值画在一个图上帮助观察
end

难度太大了 我不会。