MATLAB: Correlation pairs

cross correlation

The following code calculates the correlation between 2 vectors:
clear all
  %generate fake data
  LName={'Name1','Name2','Name3'};
  Data={rand(12,1),rand(12,1),rand(12,1)};
  %place in a structure
  d = [LName;Data];
  Data = struct(d{:});
  %find the correlation
  SNames=fieldnames(Data);
  pairs = combnk (1:numel(SNames),2); 
  for i = 1 : size (pairs,1)
     [R{i},P{i}] = corrcoef(Data.(SNames{pairs(i,1)}),Data.(SNames{pairs(i,2)}));  
     Correlation{i}=R{i}(1,2);
  end
However, I want to find the correlation between all possible combinations. So, not just calculate the correlation between 2 elements but between 2 and then between 3… and so on. I can find the correlation between 3 elements by changing the line:
   pairs = combnk (1:numel(SNames),3);
to
for i = 1:length(fieldnames(Data));
    pairs.(SNames{i,1}) = combnk (1:numel(SNames),i);
end
But I want to adapt this to not just list the names from 'SNames' but to write which combinations i.e. SName1 v SName2.

Best Answer

I think that You not need doing this. I'm offering the following variant:
LName={'Name1','Name2','Name3'};
Dat={rand(12,1),rand(12,1),rand(12,1)};
d = [LName;Dat];
Data = struct(d{:});
d1 = cell2mat(struct2cell(Data)');
[R,P] = corrcoef(d1);
Correlation = [LName(nchoosek(1:size(R,1),2)) num2cell(nonzeros(tril(R,-1)))]
OR
R = corrcoef([Dat{:}]);
Correlation = [nchoosek(1:size(R,1),2) nonzeros(tril(R,-1))]
OR
Correlation = sparse(tril(R,-1))
ADD eg:
>> LName={'Name1','Name2','Name3' 'Name4'};
Dat={rand(12,1),rand(12,1),rand(12,1),rand(12,1)};
R = corrcoef([Dat{:}])
Correlation = [LName(nchoosek(1:size(R,1),2)) num2cell(nonzeros(tril(R,-1)))]
R =
            1      0.62864      0.50105    -0.066267
      0.62864            1      0.20848   -0.0042032
      0.50105      0.20848            1      0.23383
    -0.066267   -0.0042032      0.23383            1
Correlation = 
    'Name1'    'Name2'    [   0.62864]
    'Name1'    'Name3'    [   0.50105]
    'Name1'    'Name4'    [ -0.066267]
    'Name2'    'Name3'    [   0.20848]
    'Name2'    'Name4'    [-0.0042032]
    'Name3'    'Name4'    [   0.23383]
>>
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