A1111
Title: Efficient estimation for scale parameter of Birnbaum Saunders distribution for multiple dimensions
Authors: Waqas Makhdoom - Department of Statistics, Government College University, Lahore (Pakistan) [presenting]
Muhammad Kashif Ali Shah - Government College University Lahore (Pakistan)
Nighat Zahra - Government College University Lahore (Pakistan)
Ejaz Ahmed - Brock (Canada)
Abstract: The Birnbaum-Saunders distribution is one of the most reputable probability distributions for fatigue life and reliability studies, having shape and scale parameters. The parameter estimation of this distribution is a common area of interest for researchers in recent times. The maximum likelihood estimation approach is generally used for point estimation due to its appealing asymptotic properties. The interest is in boosting the efficiency of the scale estimator while incorporating non-sample information. Some improved estimation strategies are employed, such as the restricted linear shrinkage estimator, the preliminary test estimator, the shrinkage preliminary test estimator, and the Stein-type shrinkage estimators. The asymptotic properties of the suggested estimators are derived both in analytical and numerical terms. The graphical presentation of the performance of the estimators is also presented. A real-life data set is analyzed to judge the performance of the proposed estimators.
