@tomgp/gaussian v1.1.2

gaussian

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

This is a fork for use with unpkg.com & so observablehq.com

API

Creating a Distribution

var gaussian = require('@tomgp/gaussian');
var distribution = gaussian(mean, variance);
// Take a random sample using inverse transform sampling method.
var sample = distribution.ppf(Math.random());

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 result of adding this and the given distribution's means and variances
• sub(d): returns the result of subtracting this and the given distribution's means and variances
• scale(c): returns the result of scaling this distribution by the given constant