Journal
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Volume 52, Issue 19, Pages 6916-6935Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610926.2022.2037642
Keywords
Length-biased model; mode regression; bimodality; Monte Carlo simulation; meteorological data
Categories
Ask authors/readers for more resources
The length-biased Birnbaum-Saunders distribution is introduced and applied in environmental sciences in this paper. New properties of the distribution are derived, showing that one of its parameters is the mode and that it is bimodal. A new regression model based on this distribution is proposed and parameter estimation is done using the maximum likelihood method. The performance of the proposed methods is evaluated through a Monte Carlo study and illustrated using a real meteorological data set.
The length-biased Birnbaum-Saunders distribution is both useful and practical for environmental sciences. In this paper, we initially derive some new properties for the length-biased Birnbaum-Saunders distribution, showing that one of its parameters is the mode and that it is bimodal. We then introduce a new regression model based on this distribution. We implement the maximum likelihood method for parameter estimation, approach interval estimation and consider three types of residuals. An elaborate Monte Carlo study is carried out for evaluating the performance of the likelihood-based estimates, the confidence intervals and the empirical distribution of the residuals. Finally, we illustrate the proposed regression model with the use of a real meteorological data set.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available