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Covariance is a quantity used to measure the strength and direction of the linear relationship between two variables. The covariance is unscaled, & thus often difficult to interpret; when scaled by the variables' SDs, it becomes Pearson's correlation coefficient.

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Concentration inequality for the sample covariance matrix

I'd like to know if there is a concentration inequality for the sample covariance matrix that don't assume the knowledge of the true mean. Background. … Given a probability distribution $\mu$ on $\mathbb R^d$, the covariance matrix of $\mu$ is defined as follows: $$\Sigma := \mathbb E [(x - \bar \mu)(x -\bar \mu)^\top] $$ where $x \sim \mu$ and $\bar \ …
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