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errcw
150 Stars 34 Forks MIT License 38 Commits 0 Opened issues

Description

A JavaScript model of the normal distribution

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gaussian

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

API

Creating a Distribution

var gaussian = require('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

Generation Function

  • random(n)
    : returns an array of generated
    n
    random samples correspoding to the Gaussian parameters.

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