Streaming implementation of multiple regression.

npm install smr
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This is an implementation of multiple regression in JavaScript. It is streaming, which means that you can incrementally add observations and recalculate coefficients on the fly, without having to re-iterate over your dataset. This is particularly useful if you want to run multiple regression in real-time or over very large datasets that won't fit into memory all at once.

Quick Start

From Node.js:

npm install smr


var Regression = require('smr').Regression

In the browser:

<script src=""></script>
<script src=""></script>


var regression = new Regression({ numX: 2, numY: 1 })

regression.push({ x: [10, 11], y: [100] })
regression.push({ x: [9, 12], y: [99] })

regression.calculateCoefficients() // Returns [[4.29], [5.29]]

regression.push({ x: [8, 15], y: [80] })
regression.calculateCoefficients() // Returns [[-0.16], [10.55]]
regression.hypothesize({ x: [1, 2] }) // Returns [20.93]


To calculate multiple regression, we use the following formula:

(X' * X) ^ -1 * X' * Y

Where X is a matrix of independent variables, X' is its transpose, Y is a matrix of dependent variables, and ^ -1 indicates taking the pseudoinverse.


Internally, we incrementally calculate the two matrix products, X' X and X' Y, in an incremental fashion as new observations are added. Whenever you request the coefficients, either through calculateCoefficients() or indirectly through hypothesize(), the library will find the pseudoinverse of the readily-available X' X (using numericjs) and multiply this by the readily-available X' Y.

For solving large-dimensional problems is real-time, the lazy pseudoinverse calculation can be a bottleneck, but it's good enough in most cases.

Unit Tests

Calculations are verified against numericjs. The unit tests use nodeunit. You can set everything up with:

git clone
cd smr
npm install
npm install -g nodeunit

Then you can run unit tests with:

nodeunit tests.js
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