@tomgp/gaussian
v1.1.2
Published
A JavaScript model of a Gaussian distribution
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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 distributionvariance
: the variance (σ^2) of the distributionstandardDeviation
: 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 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
Combination Functions
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