function mx = nanmean(x)%NANMEAN  Mean of available data, ignoring NaNs.%%    NANMEAN(X) returns the mean of the available data in X, treating%    NaNs as missing values. For vectors, NANMEAN(X) is the mean value%    of the non-NaN elements in X.  For matrices, NANMEAN(X) is a row%    vector containing the mean value of each column, ignoring NaNs.%%    If, in forming the mean, the fraction of missing terms exceeds%    a critical value, the mean is set to NaN.%  %    See also MEAN, NANSTD, NANSUM.  % maximum admissible fraction of missing values  max_miss = 0.99;                    error(nargchk(1,1,nargin))          % check number of input arguments   if isempty(x)                       % check for empty input.    mx = NaN;    return  end  % if x is vector, make sure it is a row vector  if length(x)==prod(size(x))             x = x(:);                           end  [m,n]   = size(x);    % replace NaNs with zeros.  inan    = find(isnan(x));  x(inan) = zeros(size(inan));    % determine number of available observations on each variable  [i,j]   = ind2sub([m,n], inan);     % subscripts of missing entries  nans    = sparse(i,j,1,m,n);        % indicator matrix for missing values  nobs    = m - sum(nans);      % set nobs to NaN when there are too few entries to form robust average  minobs  = m * (1 - max_miss);  k       = find(nobs < minobs);  nobs(k) = NaN;    mx      = sum(x) ./ nobs;