# godist

`godist`

provides some Go implementations of useful continuous and discrete probability distributions, as well as some handy methods for working with them.

The general idea is that I will add to these over time, but that each distribution will implement the following interface:

```
type Distribution interface{
// distribution mean
Mean() (float64, error)
// distribution median
Median() (float64, error)
// distribution mode
Mode() (float64, error)
// distribution variance
Variance() (float64, error)
// generate a random value according to the probability distribution
Float64() (float64, error)
}
```

In practice, distributions may also provide other useful methods, where appropriate.

The intentions of `godist`

is not to provide the fastest, most efficient implementations, but instead to provide idiomatic Go implementations that can be easily understood and extended. Having said that, where there are useful and well-understood numerical tricks and tools to improve performance, these have been utilised and documented.

Contributions welcome!

### Current Distributions

- Beta Distribution
- Empirical Distribution