2024/03/26 by Prajapat, Kiran, Mitra, Sharmishtha, Kundu, Debasis
#Computation (stat.CO) #FOS: Computer and information sciences #Methodology (stat.ME)
paper · doi:10.48550/arxiv.2403.17609
In numerous instances, the generalized exponential distribution can be used as an alternative to the gamma distribution or the Weibull distribution when analyzing lifetime or skewed data. This article offers a consistent method for estimating the parameters of a three-parameter generalized exponential distribution that sidesteps the issue of an unbounded likelihood function. The method is hinged on a maximum likelihood estimation of shape and scale parameters that uses a location-invariant statistic. Important estimator properties, such as uniqueness and consistency, are demonstrated. In addition, quantile estimates for the lifetime distribution are provided. We present a Monte Carlo simulation study along with comparisons to a number of well-known estimation techniques in terms of bias and root mean square error. For illustrative purposes, a real-world lifetime data set is analyzed.