MATLAB: How to efficiently find the mean and covariance of a cell containing matrices with different rows

cell arrays

I have a 1×15 cell which contains 15 matrices, and each of them has different number of rows but all have the same number of columns(14). I am trying to find the mean and covariance of the whole cell. I compute them by concatenating all matrices into a big matrix and use the built-in functions to get the result, which looks like this:
 M = C{1};
 for i=2:15
    M = [M; C{i}];
 end
 mean = mean(M);
 cov = cov(M);
I think this approach does not fully take advantage of the flexibility of cells. Is there a more efficient way to do that?

Best Answer

Use concatenate to mix up all cells into one matrix.
cat(2,C{:}); %you can use this only if number of rows must be same in all cells
or
cat(1,C{:});  %for your data
After using cat, calculate mean and cov in usual manner.
As your data have the different number of rows in all cells, you cannot use cat(2,C{:}).
Related Question