correl-z

correlated standard normal distribution random number generator

• Example • API • License

Example

var correlZ = require('correlZ'),
    randomZ = require('random-z'), // unit normal distribution random number generator
    cholesky = require('cholesky') // cholesky decomposition

var correlMatrix = [[1], [0.2, 1], [0.2, 0.2, 1]] // lower triangle is enough
    correlWeights = cholesky(correlMatrix),
    correlSeeders = correlWeights.map(correlZ) // array of random number generators

var iids = correlWeights.map(randomZ) // shared identically distributed variables

// all 3 results below are different but correlated, E=0, V=1, Cor(i,j) = 0.2
var x0 = correlSeeder[0](iids),
    x1 = correlSeeder[1](iids),
    x2 = correlSeeder[2](iids)

API

The module exports a single function that takes an array of linear factors or a key-factor object to be applied to shared standard normal Independent and identically distributed random_variables (iids) and returns a standard normal correlated random number generator.

Name | Type | Notes / Examples :--- | :--- | :------ correlZ | weights => randomFcn | rand = correlZ({2:0.1, 1:0.2}) weights | Object | Array | Σv²<1: {1:0.2}, [0, 0.2], {a: 0.2} randomFcn | (iidZs [,selfZ]) => Number | Zi<1: sample = randomFcn({a:0.7, b:0.4}) iidZs | Object | Array of zSeed | {a:0.7, b:0.4} selfZ | zSeed | optional standard normal seed for testing. Normally generated internally zSeed | Number | standard normal random seed -1 < v < 1

Note that the linear iid weights can obtained from the correlation matrix with the cholesky module.

License

MIT © Hugo Villeneuve