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The relationship between covariance, standard deviation and correlation is: $$ corr(x,y) = \frac{cov(x,y)}{\sigma_x \sigma_y}$$ So to construct your matrix you will have the variances in the diagonal: $$ cov(x,x) = corr(x,x) \times \sigma_x \times \sigma_x = 1 \times \sigma_x^2 = \sigma_x^2 $$ And for the covariances: $$ cov(x,y) = corr(x,y) \times \...


here is how to get covariance matrix from correlations:

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