Related Experiment Video
Updated: Nov 18, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
Published on: August 16, 2017
Estimation for Entropy and Parameters of Generalized Bilal Distribution under Adaptive Type II Progressive Hybrid
Xiaolin Shi1, Yimin Shi2, Kuang Zhou2
1School of Electronics Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Abstract:
Entropy measures the uncertainty associated with a random variable. It has important applications in cybernetics, probability theory, astrophysics, life sciences and other fields. Recently, many authors focused on the estimation of entropy with different life distributions. However, the estimation of entropy for the generalized Bilal (GB) distribution has not yet been involved. In this paper, we consider the estimation of the entropy and the parameters with GB distribution based on adaptive Type-II progressive hybrid censored data. Maximum likelihood estimation of the entropy and the parameters are obtained using the Newton-Raphson iteration method. Bayesian estimations under different loss functions are provided with the help of Lindley's approximation. The approximate confidence interval and the Bayesian credible interval of the parameters and entropy are obtained by using the delta and Markov chain Monte Carlo (MCMC) methods, respectively. Monte Carlo simulation studies are carried out to observe the performances of the different point and interval estimations. Finally, a real data set has been analyzed for illustrative purposes.
Related Concept Videos
Censoring Survival Data
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Kaplan-Meier Approach
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...

