Wilcoxon test

 

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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

　　

 

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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