# gaussian

A JavaScript model of a Gaussian distribution

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gaussian
17001.3.018 days ago11 years ago

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.