A study on methods for estimating the PDF and the CDF in the exponentiated gamma distribution

The exponentiated gamma distribution is a two parameters lifetime distribution with monotone and non-monotone failure rates. In this article, some estimation methods of the probability density function and the cumulative distribution function of the exponentiated gamma distribution such as uniformly...

Full description

Saved in:
Bibliographic Details
Published in:Communications in statistics. Simulation and computation 2020-08, Vol.49 (8), p.1999-2013
Main Author: Rasekhi, Mahdi
Format: Article
Language:English
Subjects:
Computer simulation
Distribution functions
Exponentiated gamma distribution
Failure rates
Least squares
Least squares estimator
Maximum likelihood estimator
Minimum distance estimator
Probabilistic methods
Probability density functions
Probability distribution functions
Statistical analysis
Uniformly minimum variance unbiased estimator
Weighted least squares estimator
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The exponentiated gamma distribution is a two parameters lifetime distribution with monotone and non-monotone failure rates. In this article, some estimation methods of the probability density function and the cumulative distribution function of the exponentiated gamma distribution such as uniformly minimum variance unbiased (UMVU), maximum likelihood (ML), least squares, weighted least squares and Minimum distance estimators are studied and their performances through numerical simulations are compared. By the mean integrated squared error (MISE), the UMVU and ML are approximately equivalent and more efficient than the others based on simulation studies when the sample size is more than 40. A real data set is analyzed for illustrative purposes.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2018.1508707