Evaluation and Comparison of Estimators in the Gompertz Distribution

Sanku Dey, Tanmay Kayal and Yogesh Mani Tripathi ()
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Sanku Dey: St. Anthony’s College
Tanmay Kayal: Indian Institute of Technology Patna
Yogesh Mani Tripathi: Indian Institute of Technology Patna

Annals of Data Science, 2018, vol. 5, issue 2, No 6, 235-258

Abstract: Abstract This article addresses the different methods of estimation of the probability density function and the cumulative distribution function for the Gompertz distribution. Following estimation methods are considered: maximum likelihood estimators, uniformly minimum variance unbiased estimators, least squares estimators, weighted least square estimators, percentile estimators, maximum product of spacings estimators, Cramér–von-Mises estimators, Anderson–Darling estimators. Monte Carlo simulations are performed to compare the behavior of the proposed methods of estimation for different sample sizes. Finally, one real data set and one simulated data set are analyzed for illustrative purposes.

Keywords: Gompertz distribution; Maximum likelihood estimator; Uniformly minimum variance unbiased estimator; Least square estimator; Percentile estimator; Cramér–von-Mises estimator; 62F10 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s40745-017-0126-z

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