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c++boostrandomgeometryboost-random

standard multivariate normal random vector using Boost::random

I would like to generate random points on a 2D surface, distributed around a x0, y0 coordinate.

I understand that what I need to generate is called "standard multivariate normal random vector", but I don't know how to do it in C++, for example using the Boost::random library.

I know there is an algorith for generating this, called Box–Muller transform but I would think that this must have already been implemented properly in Boost.

Is there any simple way to generate multivariate normal distribution, using Boost::random?

Solution

  • It seems to be:

    // deterministic Box-Muller method, uses trigonometric functions
template<class RealType = double>
class normal_distribution
{

    But Box-Muller isn't 2D. All you really have to do to get the 2D version is to take the two random numbers generated and add them to the x0, y0 coordinates.