statistical-js
v2.1.0
Published
Simple to use, completely useful
Downloads
101
Maintainers
Readme
Library that provide you some statistics which are useful and with the best performance execution.
Getting Started
npm install --save statistcal-js
import the library :
/* how to import and use it */
const statistical = require('statistical-js');
use statistical methods :
const res = statistical.methods.sum([1, 2, 3]);
or use machine learning methods :
const p = new statistical.ml.Perceptron({
learningRate: 0.3,
bias: 0.5
});
Performance
To provide you with the best performance when using statistical-js, this library has implemented a variable cache system to save the last calculations. To see how manage it if it necessary, you can go to perfomance section !
Actually supported
Click there see the complete documentation.
Simple statistics
- Min
- Max
- Sum
- Median
- Mode
- Mean
- Variance
- Standard deviation
- Quantile
- Summary (regroup all descriptives statistics above)
- Percentile
- Factorial
- Geometric mean
- Harmonic mean
- InterQuartileRange
- Sample variance (Non biased variance)
- Sample Standard deviation (Non biased std deviation)
Advanced statistics
- Covariance
- Binomial
- Bernoulli
- Poisson
- Chi Squared Goodness Of Fit
- T-test - one sample (t-value)
- T-test - two sample (t-value)
- Linear regression (slope, intersect)
Machine learning
- Perceptron (Single layer)
As soon as possible, more features will be available.
Test
To run test without coverage.
npm run test
If you want to generate coverage in ./coverage
.
npm run test:coverage
Lint
The command to lint code and fix it at the same time
npm run lint
build
To build dev version ./lib/statistical.js
npm run dev
If you want to generate the production version ./lib/statistical.min.js
npm run build
License
This project is licensed under the MIT License - see the LICENSE.md file for details