The ti(exponential_distribution<RealType = double>) is used to describe the
lengths between events that can be modeled with a homogeneous Poisson
process. It can be interpreted as the continuous form of the
geometric distribution.

Its parameter tt(prob) defines the distribution's em(lambda) parameter, called
its em(rate) parameter. Its expected value and standard deviation are both
tt(1 / lambda).

Defined types:
        verb(    using result_type = RealType;

    struct param_type
    {
        explicit param_type(RealType lambda = RealType(1));

        RealType lambda() const;
    };)

Constructors and members:
    itemization(
    itt(exponential_distribution<>(RealType lambda = 1))
       constructs an exponential distribution with specified tt(lambda)
        parameter.
    itt(exponential_distribution<>(param_type const &param))
       constructs an exponential distribution according to the value stored in
        the tt(param) struct.
    itt(RealType lambda() const)nl()
        returns the distribution's tt(lambda) parameter;
    itt(result_type min() const)nl()
        returns 0;
    itt(result_type max() const)nl()
        returns the maximum value of tt(result_type);
    )
