A JavaScript model of the Normal (or Gaussian) distribution.
var gaussian = require('gaussian');
var distribution = gaussian(mean, variance);
// Take a random sample using inverse transform sampling method.
var sample = distribution.ppf(Math.random());mean: the mean (μ) of the distributionvariance: the variance (σ^2) of the distributionstandardDeviation: the standard deviation (σ) of the distribution
pdf(x): the probability density function, which describes the probability of a random variable taking on the value xcdf(x): the cumulative distribution function, which describes the probability of a random variable falling in the interval (−∞, x]ppf(x): the percent point function, the inverse of cdf
mul(d): returns the product distribution of this and the given distribution; equivalent toscale(d)when d is a constantdiv(d): returns the quotient distribution of this and the given distribution; equivalent toscale(1/d)when d is a constantadd(d): returns the result of adding this and the given distribution's means and variancessub(d): returns the result of subtracting this and the given distribution's means and variancesscale(c): returns the result of scaling this distribution by the given constant
random(n): returns an array of generatednrandom samples correspoding to the Gaussian parameters.