Conversion of covariances to correlations

Source: R/cov_cor_conversion.R

Use the function `base::cov2cor()` to convert a variance-covariance matrix to a correlation matrix

cov_to_cor(V)

Arguments

V

symmetric positive definite variance-covariance matrix

Value

correlation matrix

Examples

## Taken from ?cov2cor: Correlation Matrix of Multivariate sample:
(Cv <- cov(longley))

#>              GNP.deflator       GNP Unemployed Armed.Forces Population
#> GNP.deflator    116.45763 1063.6041   625.8666     349.0254   73.50300
#> GNP            1063.60412 9879.3537  5612.4370    3088.0428  685.24094
#> Unemployed      625.86663 5612.4370  8732.2343   -1153.7876  446.27415
#> Armed.Forces    349.02537 3088.0428 -1153.7876    4843.0410  176.40981
#> Population       73.50300  685.2409   446.2742     176.4098   48.38735
#> Year             50.92333  470.9779   297.3033     138.2433   32.91740
#> Employed         36.79666  343.3302   164.9103     111.7681   23.46197
#>                   Year  Employed
#> GNP.deflator  50.92333  36.79666
#> GNP          470.97790 343.33021
#> Unemployed   297.30333 164.91027
#> Armed.Forces 138.24333 111.76811
#> Population    32.91740  23.46197
#> Year          22.66667  16.24093
#> Employed      16.24093  12.33392
stopifnot(all.equal(cov2cor(Cv), cor(longley)))