scipy.stats.cov(m, y=None, rowvar=False, bias=False)

Estimate the covariance matrix.

If m is a vector, return the variance. For matrices where each row is an observation, and each column a variable, return the covariance matrix. Note that in this case diag(cov(m)) is a vector of variances for each column.

cov(m) is the same as cov(m, m)

Normalization is by (N-1) where N is the number of observations (unbiased estimate). If bias is True then normalization is by N.

If rowvar is False, then each row is a variable with observations in the columns.

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