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Compute the gini coefficient of the numeric data, with small sample correction.
var giniSS = require('gini-ss');
giniSS([0,0,0,0,1]) // --> 1.0
giniSS([0,0,0]) // --> 0.0
giniSS([3,3,3]) // --> 0.0
giniSS([1,2,3,...,100]) // --> ~ 99/303 ~ 1/3
The Gini coefficient with small sample correction has a value of 1.0 for the case of perfect inequality, when
for example, with income data, all of the incomes are zero and one person has all the income.
The traditional Gini instead yields G = 1-(1/n) = (n-1)/n
. The correction is simply multiplying by n/(n-1)
These converge as the number of samples n become large.
For more information, see the Wikipedia article for Gini coefficient
Copyright 2017 Paul Brewer, Economic and Financial Technology Consulting LLC
FAQs
compute Gini coefficient with small sample correction
The npm package gini-ss receives a total of 7 weekly downloads. As such, gini-ss popularity was classified as not popular.
We found that gini-ss demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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