The Pareto and the Log-normal distributions can be characterised by having constant inequality curves. After providing formal proofs, these results will be exploited to obtain graphical and analytical tools for analysis and goodness-of-fit tests for these distributions. Order- statistics-based estimators of the curves will be presented and discussed. Examples with simulated and real-data will be used to show how the tools presented work in practice.

Graphical representations and associated goodness-of-fit tests for Pareto and log-normal distributions based on inequality curves

Santi, Flavio;
2021

Abstract

The Pareto and the Log-normal distributions can be characterised by having constant inequality curves. After providing formal proofs, these results will be exploited to obtain graphical and analytical tools for analysis and goodness-of-fit tests for these distributions. Order- statistics-based estimators of the curves will be presented and discussed. Examples with simulated and real-data will be used to show how the tools presented work in practice.
tail index, Pareto tail graphical analysis, nonparametric estimation, parametric bootstrap
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/1049569
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