The ti(fisher_f_distribution) 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( typedef RealType result_type; 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 ¶m)) 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); )