import Distribution from 'sampson/lib/distributions/distribution.js'

public interface | source

Distribution

Direct Subclass:

Binomial, Cauchy, ChiSquared, Exponential, Gamma, Normal, StudentsT

Indirect Subclass:

Bernoulli

An abstract Distribution class. All of our Distributions extend this. It holds the base uniform random number generator.

Static Method Summary

Static Public Methods
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.

Constructor Summary

Public Constructor
public	constructor(params: Object) A generic distribution constructor.

Member Summary

Public Members
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.

Method Summary

Public Methods
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.

Static Public Methods

public static random(): number source

Generate a uniform random variable.

Return:

number

A uniform random variable.

public static sample(k: number, params: Object): Array<number> source

Generate an array of k random values.

Params:

Name	Type	Attribute	Description
k	number		The number of values to generate.
params	Object		The distribution parameters.

Return:

Array<number>

An array of k random values.

Public Constructors

public constructor(params: Object) source

A generic distribution constructor.

Params:

Name	Type	Attribute	Description
params	Object		The distribution parameters.

Public Members

public kurtosis: number source

The distribution kurtosis.

public mean: number source

The distribution mean.

public params: Object source

The valitated distribution parameters.

public relStdDev: number source

The distribution relative standard deviation.

public skewness: number source

The distribution skewness.

public stdDev: number source

The distribution standard deviation.

public variance: number source

The distribution variance.

Public Methods

public cdf(x: number): number source

Calculate the probability of getting x or less.

Params:

Name	Type	Attribute	Description
x	number		The value to predict.

Return:

number

The probability of getting x or less.

public pdf(x: number): number source

Calculate the probability of exaclty x.

Params:

Name	Type	Attribute	Description
x	number		The value to predict.

Return:

number

The probability of x occuring.

public random(): number source

Generate a random value.

Return:

number

The random value.

public sample(n: number): Array<number> source

Generate an array of n random values.

Params:

Name	Type	Attribute	Description
n	number		The number of values to generate.

Return:

Array<number>

An array of n random values.