Second order efficiency of the MLE with respect to any bounded bowl- shaped loss function
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Publication:1140941
DOI10.1214/aos/1176345005zbMath0436.62031OpenAlexW2152075907MaRDI QIDQ1140941
Bimal Kumar Sinha, Harry S. Wieand, Jayanta K. Ghosh
Publication date: 1980
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1176345005
Rao-Blackwell theoremEdgeworth expansionBayes testmaximum likelihood estimatesecond order efficiencybounded bowl-shaped loss function
Asymptotic properties of parametric estimators (62F12) Statistical aspects of information-theoretic topics (62B10)
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Second order asymptotic optimality of estimators for a density with finite cusps ⋮ The second-order bias and mean squared error of nonlinear estimators ⋮ Higher order asymptotics in estimation for two-sided Weibull type distributions ⋮ Information amount and higher-order efficiency in estimation ⋮ Minimum Divergence, Generalized Empirical Likelihoods, and Higher Order Expansions ⋮ The 3/2th and 2nd order asymptotic efficiency of maximum probability estimators in non-regular cases ⋮ The Professional Career and Contributions of Professor Masafumi Akahira ⋮ A third-order optimum property of the maximum likelihood estimator ⋮ Addendum to ``A third-order optimum property of the maximum likelihood estimator ⋮ A third order optimum property of the ML estimator in a linear functional relationship model and simultaneous equation system in econometrics ⋮ More higher-order efficiency: Concentration probability ⋮ Sam Wieand at the University of Pittsburgh ⋮ Edgeworth expansions for GEL estimators ⋮ Saddlepoint expansions for GEL estimators
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