A Python Based Library to Calculate Estimators (Sn, Qn, MAD, IQR)
Project description
robustbase
A Python Library to Calculate Estimators.
Installation
OS X , Windows & Linux:
pip install robustbase
Usage example
This package is used to calculate the following statistical estimators.
- Qn scale estimator
- Sn scale estimator
- Median Absolute Deviation(MAD)
- Interquartile Range (IQR)
from robustbase import Qn, Sn, mad, iqr
import numpy as np
data = np.random.rand(10)
print(Qn(data))
print(Sn(data))
print(mad(data))
print(iqr(data))
Development setup
For local development setup
git clone https://github.com/deepak7376/robustbase
cd robustbase
pip install -r requirements.txt
Meta
Deepak Yadav – @imdeepak_dky – dky.united@gmail.com
Distributed under the MIT license. See LICENSE
for more information.
https://github.com/deepak7376/robustbase/blob/master/LICENSE
Contributing
- Fork it (https://github.com/deepak7376/robustbase/fork)
- Create your feature branch (
git checkout -b feature/fooBar
) - Commit your changes (
git commit -am 'Add some fooBar'
) - Push to the branch (
git push origin feature/fooBar
) - Create a new Pull Request
References
https://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/qn_scale.htm https://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/sn_scale.htm https://www.statisticshowto.datasciencecentral.com/median-absolute-deviation/ https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/interquartile-range/
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for robustbase-0.2.6-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | baac02f5147c9279677678320d356c4755bc98b2300e7ba20396ef3fad64a8ed |
|
MD5 | fbcafc2abe7045db2409498bc405c351 |
|
BLAKE2b-256 | 5973fd661dbf802cf25db06c1f87b20fd4f456bd67881666a4d9dd53db3f7100 |