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;
2021-01-01

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.
2021
tail index, Pareto tail graphical analysis, nonparametric estimation, parametric bootstrap
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1049569
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact