Modified Maximum Likelihood Estimation for Generalized Exponential Distribution

Alok Kumar Singh *

Department of Statistics, Raja Balwant Singh Degree College, Agra, India.

Rohit Patawa

Department of Community Medicine, Autonomous State Medical College, Firozabad, India.

Abhinav Singh

Rajiv Gandhi South Campus, Banaras Hindu University, Mirzapur, India.

Puneet Kumar Gupta

ICFAI Business School, ICFAI University, Dehradun, India.

*Author to whom correspondence should be addressed.


Abstract

For a Modified Maximum Likelihood Estimate of the parameters of generalized exponential distribution (GE), a hyperbolic approximation is used instead of linear approximation for a function which appears in the Maximum Likelihood equation. This estimate is shown to perform better, in accuracy and simplicity of calculation, than the one based on linear approximation for the same function. Numerical computation for random samples of different sizes from generalized exponential distribution (GE), using type II censoring is done and is shown to be better than that obtained by Lee et al. [1].

Keywords: Asymptotic variance, order statistics, outliers, hyperbolic approximation, censoring, GE


How to Cite

Singh, Alok Kumar, Rohit Patawa, Abhinav Singh, and Puneet Kumar Gupta. 2021. “Modified Maximum Likelihood Estimation for Generalized Exponential Distribution”. Asian Journal of Probability and Statistics 14 (3):48-59. https://doi.org/10.9734/ajpas/2021/v14i330332.

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