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 generatedn
random samples correspoding to the Gaussian parameters.