Histogram-Based Interpolation of the Lorenz Curve and Gini Index for Grouped Data
In grouped data, the estimation of the Lorenz curve without taking into account the within-class variability leads to an overestimation of the curve and an underestimation of the Gini index. We propose a new strictly convex estimator of the Lorenz curve derived from a linear interpolation-based approximation of the cumulative distribution function. Integrating the Lorenz curve, a correction can be derived for the Gini index that takes the intraclass variability into account.
Year of publication: |
2012
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Authors: | Tillé, Yves ; Langel, Matti |
Published in: |
The American Statistician. - Taylor & Francis Journals, ISSN 0003-1305. - Vol. 66.2012, 4, p. 225-231
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Publisher: |
Taylor & Francis Journals |
Saved in:
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