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This article is cited in 11 scientific papers (total in 11 papers)
On asymptotically efficient statistical inference for moderate
deviation probabilities
M. S. Ermakov Institute of Problems of Mechanical Engineering, Russian Academy of Sciences
Abstract:
We study the lower bounds of efficiency for the moderate deviation probabilities
of tests and estimators. These bounds cover both the logarithmic
and strong asymptotics.
For the problems of hypothesis testing we propose a natural representation for
the lower bounds of type I
and type II error probabilities in terms of inverse function of
the standard normal distribution. The lower bounds for the
moderate deviation probabilities of estimators are deduced easily from
the corresponding bounds in hypothesis testing.
Keywords:
large deviations, moderate deviations, efficiency, Bahadur efficiency, Chernoff efficiency.
Received: 23.12.2002
Citation:
M. S. Ermakov, “On asymptotically efficient statistical inference for moderate
deviation probabilities”, Teor. Veroyatnost. i Primenen., 48:4 (2003), 676–700; Theory Probab. Appl., 48:4 (2004), 622–641
Linking options:
https://www.mathnet.ru/eng/tvp251https://doi.org/10.4213/tvp251 https://www.mathnet.ru/eng/tvp/v48/i4/p676
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