npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

regression-fork-norounding

v1.4.0-11

Published

Javascript least squares data fitting methods - without rounding equation strings

Downloads

7

Readme

regression.js is a javascript library containing a collection of least squares fitting methods for finding a trend in a set of data. It currently contains methods for linear, exponential, logarithmic, power and polynomial trends.

Usage

Most regressions require only two parameters - the regression method (linear, exponential, logarithmic, power or polynomial) and a data source. A third parameter can be used to define the degree of a polynomial when a polynomial regression is required.

All models will return an object with the following properties:

  • equation an array containing the coefficients of the equation
  • string A string representation of the equation
  • points an array containing the predicted data
  • r2 the coefficient of determination

Linear regression

equation: [gradient, y-intercept] in the form y = mx + c

var data = [[0,1],[32, 67] .... [12, 79]];
var result = regression('linear', data);
var slope = result.equation[0];
var yIntercept = result.equation[1];

Linear regression through the origin

equation: [gradient] in the form y = mx

var data = [[0,1],[32, 67] .... [12, 79]];
var result = regression('linearThroughOrigin', data);

Exponential regression

equation: [a, b] in the form y = ae^bx

Logarithmic regression

equation: [a, b] in the form y = a + b ln x

Power law regression

equation: [a, b] in the form y = ax^b

Polynomial regression

equation: [a0, .... , an] in the form a0x^0 ... + anx^n

var data = [[0,1],[32, 67] .... [12, 79]];
var result = regression('polynomial', data, 4);

Lastvalue

Not exactly a regression. Uses the last value to fill the blanks when forecasting.

Filling the blanks and forecasting

var data = [[0,1], [32, null] .... [12, 79]];

If you use a null value for data, regression-js will fill it using the trend.

Options


degree

The highest term in the polynomial when expressed in its canonical form. This can be any integer.

fill

Use this option to replace null values.

  • 'prev' fills null values with the preceding value
  • 'next' fills null values with the succeeding value

Alternatively, supplying this option with an integer will replace all null values with that integer.