In statistics, the precision matrix or concentration matrix is the matrix inverse of the covariance matrix or dispersion matrix, P = Σ − 1 {\displaystyle P=\Sigma ^{-1}} . For univariate distributions, the precision matrix degenerates into a scalar precision, defined as the reciprocal of the variance, p = 1 σ 2 {\displaystyle p={\frac {1}{\sigma ^{2}}}} .
In statistics, the precision matrix or concentration matrix is the matrix inverse of the covariance matrix or dispersion matrix, P = Σ − 1 {\displaystyle P=\Sigma ^{-1}} . For univariate distributions, the precision matrix degenerates into a scalar precision, defined as the reciprocal of the variance, p = 1 σ 2 {\displaystyle p={\frac {1}{\sigma ^{2}}}} .
Source: Wikipedia "Precision (statistics)" · CC BY-SA 4.0
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