c = nancov (x) returns the covariance matrix of the columns of x, treating each row as an observation, after removing NaN values. If x is a vector, the scalar variance of its non-NaN elements is returned.

c = nancov (x, y), where x and y are of equal length, is equivalent to nancov ([x(:), y(:)]) and returns the 2-by-2 covariance matrix.

c = nancov (…, normalization) specifies the normalization. When normalization is 0 (default), the covariance is normalized by $N-1$, where $N$ is the number of observations used. When it is 1, it is normalized by $N$.

c = nancov (…, method) selects how NaN values are handled. With "complete" (the default), any row of the data that contains a NaN value is removed before the covariance is computed. With "pairwise", each element c(i,j) is computed using all rows in which both column i and column j are non-NaN; the resulting matrix may fail to be positive semidefinite.

See also: cov, nanvar, nanstd, nanmean

Source Code: nancov