Modified Maximum Likelihood Estimation for Generalized Exponential Distribution
Alok Kumar Singh, Rohit Patawa, Abhinav Singh, Puneet Kumar Gupta
Asian Journal of Probability and Statistics · pp. 48–59 · Published 4 Sep 2021
10.9734/ajpas/2021/v14i330332Abstract
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].
Cited by 0
No indexed citations yet.
Related research
- TL-Moments and LQ-Moments of the Exponentiated Pareto Distribution — shares topic coverage
- Type II Half Logistic Rayleigh Distribution: Properties and Estimation Based on Censored Samples — shares topic coverage
- Exponentiated Transmuted Generalized Inverse Weibull Distribution a Generalization of the Generalized Inverse Weibull Distribution — shares topic coverage
- The Length-Biased Weighted Erlang Distribution — shares topic coverage
- The Topp Leone Generalized Inverted Kumaraswamy Distribution: Properties and Applications — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
0
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.