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https://github.com/axiomhq/variance
Go implementation of variance's method for one-pass variance computation with D. H. D. West improved methods which features merging of several multiple sets of statistics and adding weighted values.
https://github.com/axiomhq/variance
go golang standard-deviation variance welford welford-online-algorithm
Last synced: about 1 month ago
JSON representation
Go implementation of variance's method for one-pass variance computation with D. H. D. West improved methods which features merging of several multiple sets of statistics and adding weighted values.
- Host: GitHub
- URL: https://github.com/axiomhq/variance
- Owner: axiomhq
- License: mit
- Created: 2021-10-20T17:38:16.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-03-13T21:50:39.000Z (6 months ago)
- Last Synced: 2024-06-19T02:25:27.046Z (3 months ago)
- Topics: go, golang, standard-deviation, variance, welford, welford-online-algorithm
- Language: Go
- Homepage: https://axiom.co
- Size: 192 KB
- Stars: 16
- Watchers: 16
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-golang-repositories - variance - pass variance computation with D. H. D. West improved methods which features merging of several multiple sets of statistics and adding weighted values. (Repositories)
README
[![Go Reference][gopkg_badge]][gopkg]
[![Workflow][workflow_badge]][workflow]
[![Latest Release][release_badge]][release]
[![License][license_badge]][license]
[Axiom](https://axiom.co) unlocks observability at any scale.
- **Ingest with ease, store without limits:** Axiom's next-generation datastore
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others, and are the perfect way to bring together data from different sources.
For more information check out the
[official documentation](https://axiom.co/docs) and our
[community Discord](https://axiom.co/discord).
## Introduction
Go implementation of variance's method for one-pass variance computation with
D. H. D. West improved methods:
> A method of improved efficiency is given for updating the mean and variance of
> weighted sampled data when an additional data value is included in the set.
> Evidence is presented that the method is stable and at least as accurate as
> the best existing updating method.
>
> -- [Updating mean and variance estimates: an improved method - D. H. D. West](https://dl.acm.org/doi/10.1145/359146.359153)
It features merging of several multiple sets of statistics and adding weighted
values.
## Quickstart
Install using `go get`:
```shell
go get github.com/axiomhq/variance
```
Import the package:
```go
import "github.com/axiomhq/variance"
```
Use the package:
```go
package main
import (
"fmt"
"github.com/axiomhq/variance"
)
func main() {
stats1 := variance.New()
stats1.Add(1)
stats1.Add(1)
stats1.Add(1)
stats1.Add(0)
stats1.Add(0)
stats1.Add(0)
fmt.Println(
stats1.Mean(),
stats1.Variance(),
stats1.StandardDeviation(),
stats1.VariancePopulation(),
stats1.StandardDeviationPopulation(),
stats1.NumDataValues(),
)
}
```
Checkout the [example](welford_example_test.go) or
[run it on pkg.go.dev](https://pkg.go.dev/github.com/axiomhq/variance#example-package).
## License
Distributed under the [MIT License](LICENSE).
[gopkg]: https://pkg.go.dev/github.com/axiomhq/variance
[gopkg_badge]: https://img.shields.io/badge/doc-reference-007d9c?logo=go&logoColor=white
[workflow]: https://github.com/axiomhq/variance/actions/workflows/push.yaml
[workflow_badge]: https://img.shields.io/github/actions/workflow/status/axiomhq/variance/push.yaml?branch=main&ghcache=unused
[release]: https://github.com/axiomhq/variance/releases/latest
[release_badge]: https://img.shields.io/github/release/axiomhq/variance.svg?ghcache=unused
[license]: https://opensource.org/licenses/MIT
[license_badge]: https://img.shields.io/github/license/axiomhq/variance.svg?color=blue&ghcache=unused