org.jquantlib.math.distributions

Class BinomialDistribution

java.lang.Object

org.jquantlib.math.distributions.BinomialDistribution

All Implemented Interfaces:

Ops.IntToDouble

public class BinomialDistribution
extends java.lang.Object
implements Ops.IntToDouble

Binomial Distribution

In probability theory and statistics, the binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. Such a success/failure experiment is also called a Bernoulli experiment or Bernoulli trial. In fact, when n = 1, the binomial distribution is a Bernoulli distribution.

The binomial distribution is the basis for the popular binomial test of statistical significance. A binomial distribution should not be confused with a bimodal distribution.

See Also:

Binomial Distribution

Constructor Summary

Constructors

Constructor and Description
BinomialDistribution(double p, int n) Constructor of the Binomial Distribution taking two arguments for initialization.

Method Summary

Modifier and Type	Method and Description
double	op(int k) Computes the probability of k successful trials.
static double	PeizerPrattMethod2Inversion(double z, long n) Given an odd integer n and a real number z it returns p such that:

Methods inherited from class java.lang.Object

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

Constructor Detail

BinomialDistribution

public BinomialDistribution(double p,
                            int n)

Constructor of the Binomial Distribution taking two arguments for initialization.

Parameters:

p - Probability of success of each trial

n - Sequence of independent yes/no experiments

Method Detail

op

public double op(int k)

Computes the probability of k successful trials.

Specified by:

op in interface Ops.IntToDouble

Parameters:

k - Number of successful trials

Returns:

Math.exp(binomialCoefficientLn(nExp, k) + k * logP + (nExp-k) * logOneMinusP);

PeizerPrattMethod2Inversion

public static double PeizerPrattMethod2Inversion(double z,
                                                 long n)

Given an odd integer n and a real number z it returns p such that:

 1 - CumulativeBinomialDistribution((n-1)/2, n, p) = CumulativeNormalDistribution(z)
 

Pre-condition: n must be odd