import Binomial from 'sampson/lib/distributions/binomial.js'

public class | source

Binomial

Extends:

Distribution → Binomial

Direct Subclass:

Bernoulli

The Binomial Distribution is a discrete probability distribution with parameters n = number of trials and p = probability of success. See: Binomial Distribution

Static Method Summary

Static Public Methods
public static	cdf(k: number, params: Object): number Calculate the probability of k or less in B(n, p).
public static	kurtosis(params: Object): number Get the kurtosis of B(n,p).
public static	mean(params: Object): number Get the mean of B(n,p).
public static	pdf(k: number, params: Object): number Calculate the probability of exaclty k in B(n, p).
public static	random(params: Object): number Generate a random value from B(n, p).
public static	relStdDev(params: Object): number Get the relative standard deviation of B(n,p).
public static	skewness(params: Object): number Get the skewness of B(n,p).
public static	stdDev(params: Object): number Get the standard deviation of B(n,p).
public static	variance(params: Object): number Get the variance of B(n,p).

Inherited Summary

From class Distribution
public static	random(): number Generate a uniform random variable.
public static	sample(k: number, params: Object): Array<number> Generate an array of k random values.
public	kurtosis: number The distribution kurtosis.
public	mean: number The distribution mean.
public	params: Object The valitated distribution parameters.
public	relStdDev: number The distribution relative standard deviation.
public	skewness: number The distribution skewness.
public	stdDev: number The distribution standard deviation.
public	variance: number The distribution variance.
public	cdf(x: number): number Calculate the probability of getting x or less.
public	pdf(x: number): number Calculate the probability of exaclty x.
public	random(): number Generate a random value.
public	sample(n: number): Array<number> Generate an array of n random values.