The ti(fisher_f_distribution<RealType = double>) is intensively used in
statistical methods like the Analysis of Variance. It is the distribution
resulting from dividing two em(Chi-squared) distributions.

It is characterized by two parameters, being the degrees of freedom of the two
chi-squared distributions.

Note that even though the distribution's parameter tt(n) usually is an
integral value, it doesn't have to be integral, as the Fisher F distribution
is constructed from Chi-squared distributions that accept a non-integral
parameter value (see also section ref(CHISQUARED)).

Defined types:
        verb(    using result_type = RealType;

    struct param_type
    {
        explicit param_type(RealType m = RealType(1),
                            RealType n = RealType(1));

        RealType m() const; // The degrees of freedom of the nominator
        RealType n() const; // The degrees of freedom of the denominator
    };)

Constructors and members:
    itemization(
    itt(fisher_f_distribution<>(RealType m = RealType(1),
                                RealType n = RealType(1)))
        constructs a fisher_f distribution with specified degrees of freedom.
    itt(fisher_f_distribution<>(param_type const &param))
        constructs a fisher_f distribution according to the values stored in
        the tt(param) struct.
    itt(RealType m() const)nl()
        returns the degrees of freedom of the nominator;
    itt(RealType n() const)nl()
        returns the degrees of freedom of the denominator;
    itt(result_type min() const)nl()
        returns 0;
    itt(result_type max() const)nl()
        returns the maximum value of tt(result_type);
    )
