com.numericalmethod.suanshu.analysis.function.special.gaussian

Class CumulativeNormalHastings

java.lang.Object

com.numericalmethod.suanshu.analysis.function.rn2r1.univariate.UnivariateRealFunction

com.numericalmethod.suanshu.analysis.function.special.gaussian.CumulativeNormalHastings

All Implemented Interfaces:

Function<Vector,java.lang.Double>, RealScalarFunction, StandardCumulativeNormal, java.io.Serializable

public class CumulativeNormalHastings
extends UnivariateRealFunction
implements StandardCumulativeNormal

Hastings algorithm is faster but less accurate way to compute the cumulative standard Normal. It has a maximum absolute error less than 7.5e-8.

See Also:

• "Hastings, C., Jr. "Approximations for Digital Computers," Princeton University Press, Princeton, NJ. 1995."
• "Abramowitz, M., and Stegun, I.A, Handbook of Mathematical Functions, National Bureau of Standards, Washington, D.C. Reprinted by Dover, New York. 1964."

, Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface com.numericalmethod.suanshu.analysis.function.Function

Function.EvaluationException

Constructor Summary

Constructors

Constructor and Description
CumulativeNormalHastings()

Method Summary

Modifier and Type	Method and Description
double	evaluate(double x) Evaluate y = f(x).

Methods inherited from class com.numericalmethod.suanshu.analysis.function.rn2r1.univariate.UnivariateRealFunction

dimensionOfDomain, dimensionOfRange, evaluate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CumulativeNormalHastings

public CumulativeNormalHastings()

Method Detail

evaluate

public double evaluate(double x)

Description copied from class: UnivariateRealFunction

Evaluate y = f(x).

Specified by:

evaluate in interface StandardCumulativeNormal

Specified by:

evaluate in class UnivariateRealFunction

Parameters:

x - x

Returns:

f(x)