Closed-Form Estimators for the Gamma Distribution Derived From Likelihood Equations

DOI10.1080/00031305.2016.1209129OpenAlexW2482654751WikidataQ58302070 ScholiaQ58302070MaRDI QIDQ5885462

Zhi-Sheng Ye, Nan Chen

Publication date: 3 April 2023

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00031305.2016.1209129

zbMATH Keywords

asymptotic efficiencyestimating equationsgeneralized gamma distributionbias-correction

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (13)

New closed-form estimator and its properties ⋮ A score-adjusted approach to closed-form estimators for the gamma and beta distributions ⋮ New closed-form estimators for weighted Lindley distribution ⋮ Closed-form estimators and bias-corrected estimators for the Nakagami distribution ⋮ New closed-form efficient estimators for a bivariate Weibull distribution ⋮ New closed‐form efficient estimator for multivariate gamma distribution ⋮ Tolerance limits under gamma mixtures: application in hydrology ⋮ Comparison of some interval estimation methods for the parameters of the gamma distribution ⋮ Efficient closed-form maximum a posteriori estimators for the gamma distribution ⋮ Weighted stochastic block model ⋮ Closed-form estimator for the matrix-variate Gamma distribution ⋮ Shrinkage estimator for scale parameter of gamma distribution ⋮ A Note on Bias of Closed-Form Estimators for the Gamma Distribution Derived From Likelihood Equations

Uses Software

• changepoint
• SPLIDA

Cites Work

• Inference in the Generalized Gamma and Log Gamma Distributions
• A Generalization of the Gamma Distribution
• The impact of a heavy-tailed service-time distribution upon the \(\text{M}/\text{GI}/s\) waiting-time distribution
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