A JavaScript model of the Normal (or Gaussian) distribution.
API Docs: https://ts-gaussian.vercel.app
import { Gaussian } from 'ts-gaussian';
const distribution = new Gaussian(0, 1);
// Take a random sample using inverse transform sampling method.
const sample = distribution.ppf(Math.random());
// 0.5071973169873031 or something similar
-
mean
: the mean (μ) of the distribution -
variance
: the variance (σ^2) of the distribution -
standardDeviation
: 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 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
-
mul(d)
: returns the product distribution of this and the given distribution; equivalent toscale(d)
when d is a constant -
div(d)
: returns the quotient distribution of this and the given distribution; equivalent toscale(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
ts-trueskill: https://github.com/scttcper/ts-trueskill
Source: https://github.com/errcw/gaussian
ES5 Fork: https://github.com/tomgp/gaussian