Package com.numericalmethod.suanshu.analysis.function.special

Class Summary

Beta	This class represents the Beta function B(x, y).
BetaRegularized	This class represents the Regularized Incomplete Beta function Bx(p, q).
BetaRegularizedInverse	This class computes the inverse of the Regularized Incomplete Beta function.
CumulativeNormal	This computes an approximation to the cumulative Normal distribution function, N(x).
CumulativeNormalInverse	This computes an approximation to the quantile function of the cumulative Normal distribution function, N-1(x) We use the Beasley-Springer-Moro algorithm.
Digamma	The digamma function is defined as the logarithmic derivative of the gamma function.
Erf	This class computes an approximation to the error function, erf(x).
Erfc	This computes an approximation to the complementary error function, erfc(x).
ErfInverse	This class computes an approximation to the inverse of the error function, erf-1(x).
Gamma	This computes an approximation to the Gamma function, Γ(z), for real numbers.
GammaLowerIncomplete	This computes an approximation to the Lower Incomplete Gamma function, γ(s, x).
GammaRegularizedP	This class represents the Regularized Incomplete Gamma P function P(s, x).
GammaRegularizedPInverse	This class represents the inverse of the Regularized Incomplete Gamma P function.
GammaRegularizedQ	This class represents the Regularized Incomplete Gamma Q function Q(s, x).
GammaUpperIncomplete	This computes an approximation to the Upper Incomplete Gamma function, Γ(s, x).
Gaussian	This computes the Gaussian function.
LogBeta	This class represents the log of Beta function log(B(x, y)).
LogGamma	This computes an approximation to the log Gamma function, log(Γ(z)), for positive real numbers.

Enum Summary

CumulativeNormal.Method	the methods available to compute the cumulative Normal
Gamma.Method	the methods available to compute Γ(z)
LogGamma.Method	the methods available to compute log(Γ(z))