Wilcoxon test

 

clear
load NPSVOR

name={'SCV1V1','SVC1VA','SVR','CSSVC','SVMOP','NNOP','ELMOP','POM',...
    'NNPOM', 'SVOREX','SVORIM','SVORIMLin','KDLOR','GPOR','REDSVM','ORBALL' };

path0={'E:\datasets-orreview\DetailedResultsREVIEW\Real\csv\',...
    'E:\datasets-orreview\DetailedResultsREVIEW\Regression\csv\'};

Index{1}=[1 2 3 4 5 12 14 22 24 16 18 20 ];
Index{2}=[6 7 8 9 10 11 13  21 23 15 17 19];

j=2 %for Discreted Ordinal Regression Data
N=length(name);
alpha =0.05;
for i=1:N
        fname= strcat(path0{j}, 'Results-', name{i},'.','csv');
        D=importdata(fname,',');
        Data=D.data;
        Z5=[]; A5=[];
        for k=1:12
            Z5=[Z5 Data(:,(Index{1}(k)-1)*3+1 )];
            A5=[A5 Data(:,(Index{1}(k)-1)*3+2 )];
        end
        DataZ5{i} = Z5;
        DataA5{i} = A5;
end
DataZ5{N+1}=AZ5';
DataZ5{N+2}=BZ5';
DataA5{N+1}=AA5';
DataA5{N+2}=BA5';
MZE5=zeros(N+2,3);
MAE5=zeros(N+2,3);

for i=1:12
    A1=zeros(20,N+2);A2=zeros(20,N+2);
    for j=1:N+2
        A1(:,j) = DataZ5{j}(:,i);
        A2(:,j) = DataA5{j}(:,i);
    end
    MZE5 = MZE5+Wilcoxon(A1,alpha);
    MAE5 = MAE5+Wilcoxon(A2,alpha);
end


j=1 %for Real Data
N=length(name);
for i=1:N
        fname= strcat(path0{j}, 'Results-', name{i},'.','csv');
        D=importdata(fname,',');
        Data=D.data;
        Zr=[]; Ar=[];
        for k=1:17
            Zr=[Zr Data(:,(k-1)*3+1 )];
            Ar=[Ar Data(:,(k-1)*3+2 )];
        end
        DataZr{i} = Zr;
        DataAr{i} = Ar;
end
DataZr{N+1}=AZr';
DataZr{N+2}=BZr';
DataAr{N+1}=AAr';
DataAr{N+2}=BAr';
MZEr=zeros(N+2,3);
MAEr=zeros(N+2,3);

for i=1:17
    A1=zeros(30,N+2);A2=zeros(30,N+2);
    for j=1:N+2
        A1(:,j) = DataZr{j}(:,i);
        A2(:,j) = DataAr{j}(:,i);
    end
    MZEr = MZEr+Wilcoxon(A1,alpha);
    MAEr= MAEr+Wilcoxon(A2,alpha);
end

MZE=[MZE5 MZEr];MAE= [MAE5 MAEr]; %final result of average rank

　　

 

function f = Wilcoxon(A,alpha)
m=size(A,2);
Sig=zeros(m,m);
for i=1:m
    for j=i:m
        x=A(:,i);
        y=A(:,j);
        [p,h,stats]=signrank(x,y,'alpha',alpha);
        %         Sig(ni,ai)=stats.signedrank;
        if mean(x)<mean(y) && h==1
            Sig(i,j)=1;
        elseif mean(x)>mean(y) && h==1
            Sig(i,j)=-1;
        else
            Sig(i,j)=0;
        end
    end
end

X=Sig-Sig';
f=[sum(X==1,2) sum(X==0,2)-1 sum(X==-1,2)];

end