Dear Fabian, I am CCing boost, because maybe some others want to read this as well and/or correct me.

On 15. Nov 2017, at 14:21, Fabian Bösch wrote:

Thanks for clarifying. While it is true that Boost.Accumulators does this, it is for the uni-variate case only, afaik. Please correct me, if I'm wrong.

I believe you can compute a multi-dimensional mean, if you feed an appropriate Boost.Accumulator with std::valarrays. Maybe there is an easier way.

Now you have multi-variate histograms for which one would probably also like to know the Covariance (rank-2 tensor), for example. Maybe this is out of scope but a general solution for this would be nice. But perhaps this would rather be addressed in another generalized accumulator library. What do you think?

I think you are right. You can compute the covariance of two variables with Boost.Accumulators: http://www.boost.org/doc/libs/1_65_0/doc/html/accumulators/user_s_guide.html... but it does not give you a full matrix for N covariates. Maybe you could contact the maintainer of Accumulators, Eric Niebler. It is a reasonable request that would fit better into Accumulators than in Histogram. Best regards, Hans