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

*x*

`cdf(x)`

: the cumulative distribution function, which describes the

*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.