An Alternative Lambert-Type Distribution for Bounded Data

Author:

Varela Héctor1ORCID,Rojas Mario A.1,Reyes Jimmy1,Iriarte Yuri A.1ORCID

Affiliation:

1. Departamento de Matemáticas, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile

Abstract

In this article, we propose a new two-parameter distribution for bounded data such as rates, proportions, or percentages. The density function of the proposed distribution, presenting monotonic, unimodal, and inverse-unimodal shapes, tends to a positive finite value at the lower end of its support, which can lead to a better fit of the lower empirical quantiles. We derive some of the main structural properties of the new distribution. We make a description of the skewness and kurtosis of the distribution. We discuss the parameter estimation under the maximum likelihood method. We developed a simulation study to evaluate the behavior of the estimators. Finally, we present two applications to real data providing evidence that the proposed distribution can perform better than the popular beta and Kumaraswamy distributions.

Funder

internal project SEMILLERO UA-2022

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference21 articles.

1. Johnson, N.L., Kotz, S., and Balakrishnan, N. (1995). Continuous Univariate Distributions, John Wiley & Sons.

2. A generalized probability density function for double-bounded random processes;Kumaraswamy;J. Hydrol.,1980

3. Semiparametric estimation and consumer demand;Blundell;J. Appl. Econom.,1998

4. Kumaraswamy distribution: Different methods of estimation;Dey;Comput. Appl. Math.,2018

5. A note on estimation in the four-parameter beta distribution;Wang;Commun.-Stat.-Simul. Comput.,2005

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