Nonparametric Confidence Intervals for Generalized Lorenz Curve using Modified Empirical Likelihood

Autor:	Ratnasingam, Suthakaran, Wallace, Spencer, Amani, Imran, Romero, Jade
Rok vydání:	2023
Předmět:	Statistics - Methodology Mathematics - Statistics Theory
Zdroj:	Computational Statistics (2023)
Druh dokumentu:	Working Paper
DOI:	10.1007/s00180-023-01431-8
Popis:	The Lorenz curve portrays the inequality of income distribution. In this article, we develop three modified empirical likelihood (EL) approaches including adjusted empirical likelihood, transformed empirical likelihood, and transformed adjusted empirical likelihood to construct confidence intervals for the generalized Lorenz ordinate. We have shown that the limiting distribution of the modified EL ratio statistics for the generalized Lorenz ordinate follows the scaled Chi-Squared distributions with one degree of freedom. The coverage probabilities and mean lengths of confidence intervals are compared of the proposed methods with the traditional EL method through simulations under various scenarios. Finally, the proposed methods are illustrated using a real data application to construct confidence intervals. Comment: 17 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2304.04124 Zobrazit plný text záznamu View this record from Arxiv