lazy-stats

online average, variance, covariance and correlation

• Example • Features • Limitations • API • License

Example

import LazyStats from 'lazy-stats'
const stat = new LazyStats(3), // for 3 random variables

stat.push(2,1,0)
stat.push([1,1,1])
stat.push(0,1,2)

const average0 = stat.ave(0),
      average1 = stat.ave(1),
      variance2 = stat.var(2),
      covariance12 = stat.cov(1,2),
      correlation20 = stat.cor(2,0)

Features

• very small code and footprint for large number of instances
• only stores the summary values (average and covariances)
• uses Welford-style online single pass variance and covariance algorithm
• less than 100 sloc, no dependencies

Limitations

• all variables must have the same number of samples, pushed at the same time
• no skew and kurtosis

API

Properties

• .N number: total samples received
• .data Float64Array: transferable memory copy = new LazyStats( main.data )

Methods

• .push(number0, number1, ...) => {number} sampleSize - add sample value(s) and returns the sampe size
• .push([number0, number1, ...]) => {number} sampleSize - add array of sample value(s) and returns the sampe size
• .ave(index) => {number} - average of a given dataset
• .var(index) => {number} - variance of a given dataset
• .dev(index) => {number} - standard deviation of a given dataset
• .cov(j, i) => {number} - covariance between two datasets
• .cor(j, i) => {number} - correlation between two datasets
• .slope(j, i) => {number} - slope for y=set[j] and x=set[i]
• .intercept(j, i) => {number} - intercept for y=set[j] and x=set[i]
• .reset() => {object} this - clears all sums and counts back to 0

License

Released under the MIT License