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ts-gaussian
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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 the inverse transform sampling method.
const sample = distribution.ppf(Math.random());
// 0.5071973169873031 or something similar
mean: the mean (μ) of the distributionvariance: the variance (σ^2) of the distributionstandardDeviation: the standard deviation (σ) of the distributionpdf(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 cdfmul(d): returns the product distribution of this and the given distribution; equivalent to scale(d) when d is a constantdiv(d): returns the quotient distribution of this and the given distribution; equivalent to scale(1/d) when d is a constantadd(d): returns the sum of the means and variances of this distribution and the given distributionsub(d): returns the difference of the means and variances of this distribution and the given distributionscale(c): returns the result of scaling this distribution by the given constantts-trueskill: https://github.com/scttcper/ts-trueskill
Source: https://github.com/errcw/gaussian
ES5 Fork: https://github.com/tomgp/gaussian
<small>4.0.3 (2025-10-05)</small>
FAQs
A TypeScript model of a Gaussian distribution
The npm package ts-gaussian receives a total of 839 weekly downloads. As such, ts-gaussian popularity was classified as not popular.
We found that ts-gaussian demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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