Q:

Generate Random Number Based on Beta Distribution using Boost

I am trying to use Boost to generate random numbers according to the beta distribution using C++. I have seen many examples online for generating random numbers according to distributions in random.hpp (e.g. this book). However, I cannot seen to translate them to use the beta distribution found in beta.hpp.
Thanks.

A:

You'll first want to draw a random number uniformly from the range (0,1). Given any distribution, you can then plug that number into the distribution's "quantile function," and the result is as if a random value was drawn from the distribution. From here:

A general method to generate random numbers from an arbitrary distribution which has a cdf without jumps is to use the inverse function to the cdf: G(y)=F^{-1}(y). If u(1), ..., u(n) are random numbers from the uniform on (0,1) distribution then G(u(1)), ..., G(u(n)) is a random sample from the distribution with cdf F(x).

So how do we get a quantile function for a beta distribution? The documentation for beta.hpp is here. You should be able to use something like this:
#include <boost/math/distributions.hpp>
using namespace boost::math;

double alpha, beta, randFromUnif; 
//parameters and the random value on (0,1) you drew

beta_distribution<> dist(alpha, beta);
double randFromDist = quantile(dist, randFromUnif);

