MATLAB: What is the difference between mean(A,’omitnan’) and nanmean(A)

arrayMATLABmatrixmeannannanmeanomitnanvector

Hi, I have a vector A (or could be a matrix) which contains finite values as well as NaNs. I want to compute the mean value of its non-NaN elements. What is the difference between mean(A,'omitnan') and nanmean(A) ? Thank you!

Best Answer

There is no practical difference for your vector.

Personally I would use mean, because nanmean is part of the Statistics Toolbox, so using it makes your code less portable.

Related Solutions

MATLAB: Correlation between two row matrices

Like that, each value of "a" is correlated to each value of "b", but applying the formula of the correlation, the correlation of two single numbers is NaN. To compute the correlation correctly, traspose the input vectors

result  = corr(a', b');

MATLAB: Error using ‘omitnan’

Check out nanmean() in the stats & machine learning toolbox.

An alternative that doesn't require any toolboxes:

nanidx = isnan(matrix(:,w)); 
mean(matrix(~nanidx,w)

Update following comments below

To compute the mean of each column of a matrix while ignoring a key value (999999),

% Create fake data
key = 999999; 
matrix = magic(10); 
matrix(randi(100,1,10)) = key; 
% Identify the columns that contain at least one 999999
isKey = matrix == key; 
colIdx = any(isKey,1); 
% Count the number of rows per column that are not 999999
rowCount = sum(~isKey); 
% Temporarily replace 999999 with 0 and calculate the column means
matrixTemp = matrix .* ~isKey; 
colMean = sum(matrixTemp)./rowCount;
% The 2nd block above can be reduced to
%    isKey = matrix == key; 
%    colMean = sum(matrix .* ~isKey)./ sum(~isKey);

Best Answer

Related Solutions

MATLAB: Correlation between two row matrices

MATLAB: Error using ‘omitnan’

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