BinomialDistribution

java.lang.Object
- smile.stat.distribution.AbstractDistribution
- - smile.stat.distribution.DiscreteDistribution
  - - smile.stat.distribution.BinomialDistribution

All Implemented Interfaces:

Distribution
```
public class BinomialDistribution
extends DiscreteDistribution
```
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 probability of getting exactly k successes in n trials is given by the probability mass function:
Pr(K = k) = _nC_k p^k (1-p)^n-k
where _nC_k is n choose k.
It is frequently used to model number of successes in a sample of size n from a population of size N. Since the samples are not independent (this is sampling without replacement), the resulting distribution is a hypergeometric distribution, not a binomial one. However, for N much larger than n, the binomial distribution is a good approximation, and widely used.
Binomial distribution describes the number of successes for draws with replacement. In constrast, the hypergeometric distribution describes the number of successes for draws without replacement.
Although Binomial distribtuion belongs to exponential family, we don't implement DiscreteExponentialFamily interface here since it is impossible and meaningless to estimate a mixture of Binomial distributions.

See Also:

HyperGeometricDistribution

Constructor Summary

Constructors
Constructor and Description

BinomialDistribution(int n, double p)
Constructor.

Constructors
Constructor and Description
`BinomialDistribution(int n, double p)` Constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double`	`cdf(double k)` Cumulative distribution function.
`double`	`entropy()` Shannon entropy of the distribution.
`int`	`getN()` Returns the parameter n, the number of experiments.
`double`	`getProb()` Returns the probability of success.
`double`	`logp(int k)` The probability mass function in log scale.
`double`	`mean()` The mean of distribution.
`int`	`npara()` The number of parameters of the distribution.
`double`	`p(int k)` The probability mass function.
`double`	`quantile(double p)` The quantile, the probability to the left of quantile is p.
`double`	`rand()` This function generates a random variate with the binomial distribution.
`double`	`sd()` The standard deviation of distribution.
`java.lang.String`	`toString()`
`double`	`var()` The variance of distribution.

Methods inherited from class smile.stat.distribution.DiscreteDistribution
likelihood, logLikelihood, logp, p, quantile

Methods inherited from class smile.stat.distribution.AbstractDistribution
inverseTransformSampling, likelihood, logLikelihood, quantile, quantile, rejection

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - BinomialDistribution
```
public BinomialDistribution(int n,
                            double p)
```
    Constructor.
    
    Parameters:
    
    p - the probability of success.
    
    n - the number of experiments.
- Method Detail
  - getProb
```
public double getProb()
```
    Returns the probability of success.
  - getN
```
public int getN()
```
    Returns the parameter n, the number of experiments.
  - npara
```
public int npara()
```
    Description copied from interface: Distribution
    
    The number of parameters of the distribution.
  - mean
```
public double mean()
```
    Description copied from interface: Distribution
    
    The mean of distribution.
  - var
```
public double var()
```
    Description copied from interface: Distribution
    
    The variance of distribution.
  - sd
```
public double sd()
```
    Description copied from interface: Distribution
    
    The standard deviation of distribution.
  - entropy
```
public double entropy()
```
    Description copied from interface: Distribution
    
    Shannon entropy of the distribution.
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object
  - p
```
public double p(int k)
```
    Description copied from class: DiscreteDistribution
    
    The probability mass function.
    
    Specified by:
    
    p in class DiscreteDistribution
  - logp
```
public double logp(int k)
```
    Description copied from class: DiscreteDistribution
    
    The probability mass function in log scale.
    
    Specified by:
    
    logp in class DiscreteDistribution
  - cdf
```
public double cdf(double k)
```
    Description copied from interface: Distribution
    
    Cumulative distribution function. That is the probability to the left of x.
  - quantile
```
public double quantile(double p)
```
    Description copied from interface: Distribution
    
    The quantile, the probability to the left of quantile is p. It is actually the inverse of cdf.
  - rand
```
public double rand()
```
    This function generates a random variate with the binomial distribution. Uses down/up search from the mode by chop-down technique for n*p < 55, and patchwork rejection method for n*p ≥ 55. For n*p < 1.E-6 numerical inaccuracy is avoided by poisson approximation.

Class BinomialDistribution

Constructor Summary

Method Summary

Methods inherited from class smile.stat.distribution.DiscreteDistribution

Methods inherited from class smile.stat.distribution.AbstractDistribution

Methods inherited from class java.lang.Object

Constructor Detail

BinomialDistribution

Method Detail

getProb

getN

npara

mean

var

sd

entropy

toString

p

logp

cdf

quantile

rand