Lazy-stats NPM

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