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https://github.com/e-dard/godist

Probability distributions and associated methods in Go
https://github.com/e-dard/godist

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Probability distributions and associated methods in Go

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godist

======



[![Build Status](https://drone.io/github.com/e-dard/godist/status.png)](https://drone.io/github.com/e-dard/godist/latest)



[![GoDoc](https://godoc.org/github.com/e-dard/godist?status.svg)](http://godoc.org/github.com/e-dard/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:



```go

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