Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution

The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah and Alzaatreh studied the best linear unbiased estimators for the location and the scale parameters of the three-parameter log-logistic model...

Full description

Saved in:
Bibliographic Details
Published inComputational and mathematical methods Vol. 2022; pp. 1 - 13
Main Authors Mateus, Ayana, Caeiro, Frederico
Format Journal Article
LanguageEnglish
Published Hoboken Hindawi 13.02.2022
Hindawi Limited
Subjects
Asymptotic methods
Asymptotic properties
Bias
Monte Carlo simulation
Parameter estimation
Random variables
Survival analysis
Online AccessGet full text

Cover

More Information
Summary:The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah and Alzaatreh studied the best linear unbiased estimators for the location and the scale parameters of the three-parameter log-logistic model. The same authors also propose a shift-invariant Hill estimator for the unknown shape parameter. In this work, we propose a new estimation method for the shape parameter. We derive its nondegenerate asymptotic behaviour and analyse its finite sample performance through a Monte Carlo simulation study. To have precise estimates, we present a method for selecting the threshold. To illustrate the improvement achieved, efficiency comparisons are also provided.
ISSN:2577-7408
2577-7408
DOI:10.1155/2022/8400130