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Generators

Uniform distribution

Continuous

uniform(size,min,max) or uniform.continuous(size,min,max)

Parameters :   size (interger)   min (real) [Optional, Default : 0]   max (real) [Optional, Default : min+1] Returns :   (Array).

var C = require('candies');
var sample = C.uniform.continuous(10,0,2);

Discrete

uniform.discrete(size,min,max)

Parameters :   size (interger)   min (integer) [Optional, Default : 0]   max (integer) [Optional, Default : min+1] Returns :   (Array).

var C = require('candies');
var sample = C.uniform.discrete(10,0,2);

Bernouli distribution

bernouli(size,p)

Parameters :   size (interger)   p (real) [Between : 0 AND 1] Returns :   (Array).

var C = require('candies');
var sample = C.bernouli(10,.3);

Binomial distribution

binomial(size,n,p)

Parameters :   size (interger)   n (interger)   p (real) [Between : 0 AND 1] Returns :   (Array).

var C = require('candies');
var sample = C.binomial(10,5,.3);

Poisson distribution

poisson(size,lambda)

Parameters :   size (interger)   lambda (real) Returns :   (Array).

var C = require('candies');
var sample = C.poisson(10,1);

Normal (Gaussian) distribution.

normal(size,m,sd) or gaussian(size,m,sd)

Parameters :   size (interger)   m (real) [Optional, Default : 0]   sd (real) [Optional, Default : 1] Returns :   (Array).

var C = require('candies');
var sample = C.normal(10,2,2);

Exponential distribution

exponential(size,lambda)

Parameters :   size (interger)   lambda (real) [Optional, Default : 1] Returns :   (Array).

var C = require('candies');
var sample = C.exponential(10,2);

Pareto distribution

pareto(size,xmin,alpha)

Parameters :   size (interger)   xmin (real)   alpha (real) Returns :   (Array).

var C = require('candies');
var sample = C.pareto(10,1000,1.5);

Urn

urn(size,values,weight)

Parameters :   size (interger)   values (Array)   weight (Array) Returns :   (Array).

var C = require('candies');

var n = 10,
    values = ['mint','orange','strawberry'],
    weight = [.2,.3,.5];

var sample = C.urn(n,values,weight);