A new bias-corrected estimator method in extreme value distributions with small sample size

This paper proposes a bias-corrected expression for maximum likelihood estimators using the sequential number-theoretic method for optimization (SNTO) to improve the efficiency and accuracy of the estimators in three extreme value distributions (EVDs). It is well known that the widely used maximum l...

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Vydané v:	Journal of statistical computation and simulation Ročník 92; číslo 18; s. 3862 - 3884
Hlavní autori:	Wang, Sirao, Fang, Kai-Tai, Ye, Huajun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 12.12.2022 Taylor & Francis Ltd
Predmet:	Bias Bias correction extreme value distribution Extreme values Maximum likelihood estimation Maximum likelihood estimators monte carlo simulation Optimization sequential number-theoretic algorithm
ISSN:	0094-9655, 1563-5163
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