The ti(gamma_distribution<RealType = double>) is used when working with data
that are not distributed according to the normal distribution. It is often
used to model waiting times.

It has two parameters, tt(alpha) and tt(beta). Its expected value is tt(alpha
* beta) and its standard deviation is tt(alpha * beta)+sups(2).


Defined types:
        verb(    using result_type = RealType;

    struct param_type
    {
        explicit param_type(RealType alpha = RealType(1),
                            RealType beta = RealType(1));

        RealType alpha() const;
        RealType beta() const;
    };)

Constructors and members:
    itemization(
    itt(gamma_distribution<>(RealType alpha = 1, RealType beta = 1))
        constructs a gamma distribution with specified tt(alpha) and tt(beta)
        parameters.
    itt(gamma_distribution<>(param_type const &param))
        constructs a gamma distribution according to the values stored in
        the tt(param) struct.
    itt(RealType alpha() const)nl()
        returns the distribution's tt(alpha) parameter;
    itt(RealType beta() const)nl()
        returns the distribution's tt(beta) parameter;
    itt(result_type min() const)nl()
        returns 0;
    itt(result_type max() const)nl()
        returns the maximum value of tt(result_type);
    )
