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

**API Docs**: https://ts-gaussian.vercel.app

## Creating a Distribution

```
import { Gaussian } from 'ts-gaussian';
const distribution = new Gaussian(0, 1);
// Take a random sample using inverse transform sampling method.
const sample = distribution.ppf(Math.random());
// 0.5071973169873031 or something similar
```

## 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 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

## See Also

**ts-trueskill**: https://github.com/scttcper/ts-trueskill

### Forked From

**Source**: https://github.com/errcw/gaussian

**ES5 Fork**: https://github.com/tomgp/gaussian