ts-gaussian

A JavaScript model of the Normal (or Gaussian) distribution.

API Docs: https://ts-gaussian.vercel.app

Creating a Distribution

import { Gaussian } from 'ts-gaussian';
const distribution = new Gaussian(0, 1);
// Take a random sample using the inverse transform sampling method.
const sample = distribution.ppf(Math.random());
// 0.5071973169873031 or something similar
Copy

Properties

• mean: the mean (μ) of the distribution
• variance: the variance (σ^2) of the distribution
• standardDeviation: the standard deviation (σ) of the distribution

Probability Functions

• pdf(x): the probability density function, which describes the probability of a random variable taking on the value x
• cdf(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

Combination Functions

• mul(d): returns the product distribution of this and the given distribution; equivalent to scale(d) when d is a constant
• div(d): returns the quotient distribution of this and the given distribution; equivalent to scale(1/d) when d is a constant
• add(d): returns the sum of the means and variances of this distribution and the given distribution
• sub(d): returns the difference of the means and variances of this distribution and the given distribution
• scale(c): returns the result of scaling this distribution by the given constant

See Also

ts-trueskill: https://github.com/scttcper/ts-trueskill

Forked From

Source: https://github.com/errcw/gaussian
ES5 Fork: https://github.com/tomgp/gaussian