Mean of every row in a double matrix without looping

Is it possible to find mean and std dev. of every row in a huge matrix with double data and a lot of NaN interspersed without looping through every row ?

A = [1 2 NaN; 4 NaN 6 ; 8 9 10]

output = 1.5
         5
         9

Answer 1

If you have the Statistics toolbox, you can use nanmean(A,2) and nanstd(A,2).

If you don't have the toolbox, you can still avoid looping by doing

 B=A;
 map=~isnan(A);
 B(~map)=0;
 N=sum(map,2);

 rowmeans = sum(B,2)./N;
 rowstds = sqrt( sum(B.^2,2)./N -rowmeans.^2 );

If A is of type sparse, however, the above may need to be modified for efficiency's sake.

Thank You !!!