vpls.m

提供了MATLAb针对光谱数据分析的PLS算法

a=xlsread('Book1.xls');
b=xlsread('Book2.xls');
c=xlsread('Book3.xls');
d=xlsread('Book4.xls');
Y=xlsread('liucheng.xls');
y1=Y([1,5,9,13,15,16,18,22],:);
e=[a b c d];
x1=e([3,21,30,40,45,48,53,65],100:800);
[m,n] = size(x1);
for k=1:m-2
for j=1:m
    x=zeros(701,1);
    y=zeros(8,1);
    for g=1:m
        if g~=j
            x=[x x1(g,:)'];
            y=[y y1(g,:)'];
        end
       
    end
        x=x(:,[2,3,4,5,6,7,8])';
        y=y(:,[2,3,4,5,6,7,8])';
        [XL,Yl,XS,YS,beta,PCTVAR,MSE,stats] = plsregress(x,y,k);
        i=x1(j,:);
        yfit = [ones(1,1) i]*beta;
        RSS = sum((Y(j,:)-yfit).^2);
        h(k)=RSS;
        
end
   f(k)=sum(h)
end
plot(f)
        
     
                                                   

i=e(75,:);
for k=1:7

    [XL,Yl,XS,YS,beta,PCTVAR,MSE,stats] = plsregress(x,y,k);
yfit = [ones(1,1) i]*beta;
RSS = sum((Y(24,:)-yfit).^2);
h(k)=RSS
end
min=min(h);
[m1,n1]=find(h==min);
[XL,Yl,XS,YS,beta,PCTVAR,MSE,stats] = plsregress(x,y,n1);
yfit = [ones(1,1) i]*beta;
plot([Y(24,:)', yfit'])
TSS = sum((Y(24,:)-mean(y)).^2);
RSS = sum((Y(24,:)-yfit).^2);
Rsquared = 1 - RSS/TSS
yfit
Y(24,:)
s=yfit-Y(24,:)
n1