Mean of every row in a double matrix without looping

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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

Accepted Answer

Matt J
Matt J on 28 Dec 2012
Edited: Matt J on 29 Dec 2012
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.

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