A JavaScript model of the normal distribution
A JavaScript model of the Normal (or Gaussian) 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());
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 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
random(n): returns an array of generated
nrandom samples correspoding to the Gaussian parameters.