Is there an R package for modified 2-sample Hotelling's T2 test (unequal covariance matrices)?

I need to compare many multivariate means. Usually, I would do this using Hotelling's T-square test statistics.

The original Hotelling's equation is: T^2 = (nxny/nx+ny) (X-Y)' S^-1 (X-Y)

where X and Y are the vector means, S is the pooled covariance matrix, and nx/y are the sample sizes.

However, an assumption of the normal Hotelling's test is that the sample covariance matrices are equal/homogeneous. I know from Box's test that this is not true for my data. These websites present a modified version of Hotelling's T-square test that does not assume equal covariance matrices:

http://www.real-statistics.com/multivariate-statistics/hotellings-t-square-statistic/hotellings-t-square-unequal-covariance-matrices/

https://ncss-wpengine.netdna-ssl.com/wp-content/themes/ncss/pdf/Procedures/NCSS/Hotellings_Two-Sample_T2.pdf

The modified equation is: T^2 = (X-Y)' ((Sx/nx) + (Sy/ny))^-1 (X-Y)

where X and Y are the vector means, Sx/y are the corresponding covariance matrices, and nx/y are the sample sizes.

I've scoured R packages to try and find one that does this modified version of the equation with no luck. Does anyone know of a package that would do this in R?