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Others call it the covariance matrix, because it is the matrix of covariances between the scalar components of the vector X.

New York: North-Holland, 1981.Covariance and correlationMatricesSummary statisticsData analysisKovarianzmatrixMatriz de covarianzaماتریس کوواریانسMatrice de variance-covarianceMatrice delle covarianzeCovariantiematrix分散共分散行列Macierz kowariancjiMatriz de covari�nciaКовариационная матрицаKovaryans matrisiКоваріаційна матрицяMa trận hiệp phương sai协方差矩阵.

building data models from only partially observed data) one wants to find the �nearest� covariance matrix to a given symmetric matrix (e.g.

Some statisticians, following the probabilist William Feller, call this matrix the variance of the random vector X, because it is the natural generalization to higher dimensions of the 1-dimensional variance.

The answer to the converse question, whether every positive semi-definite matrix is a covariance matrix, is "yes." To see this, suppose M is a p×p positive-semidefinite matrix.

Let \mathbf{X} be any p×1 column vector-valued random variable whose covariance matrix is the p×p identity matrix.