WSEAS Transactions on Mathematics
Print ISSN: 1109-2769, E-ISSN: 2224-2880
Volume 23, 2024
Simulation Assessment of Expectation-maximization Algorithm in Pseudo-convex Mixtures Generated by the Exponential Distribution
Authors: , ,
Abstract: The use of pseudo-convex mixtures generated from stable distributions for extremes offers a valuable
approach for handling reliability-related data challenges. This framework encompasses pseudo-convex mixtures
stemming from exponential distribution. However, precise parameter estimation, particularly in cases where the
weight parameter ω is negative, remains a challenge. This work assesses the performance of the Expectation-
Maximization algorithm in estimating parameters for pseudo-convex mixtures generated by the exponential distribution
through simulation.