On parameter estimation for Amoroso family of distributions

Catherine Combes and Hon Keung Tony Ng

Mathematics and Computers in Simulation (MATCOM), 2022, vol. 191, issue C, 309-327

Abstract: The four-parameter generalized gamma (GΓ) distribution, also known as the Amoroso family of distributions, is a flexible and versatile statistical distribution that encapsulates many well-known lifetime distributions, including the exponential, Weibull, lognormal, and gamma distributions as special instances. The four-parameter GΓ distribution is shown to be appropriate for fitting skewed and heavy-tailed data sets. However, even though the GΓ distribution is very useful and flexible, it remains less studied than its counterparts, probably due to the difficulty in estimating the parameters of the distribution. In this paper, we explore several novel iterative parameter estimation approaches for the four-parameter GΓ distribution, which includes the maximum likelihood estimation and minimum distance estimation approaches.

Keywords: Maximum likelihood estimation; Minimum distance estimation; Optimization; Generalized gamma distribution (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:191:y:2022:i:c:p:309-327

DOI: 10.1016/j.matcom.2021.07.004

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