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Titlebook: Asymptotic Expansions for General Statistical Models; Johann Pfanzagl Book 1985 Springer-Verlag Berlin Heidelberg 1985 approximation.behav

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21#
發(fā)表于 2025-3-25 06:29:12 | 只看該作者
22#
發(fā)表于 2025-3-25 10:26:18 | 只看該作者
23#
發(fā)表于 2025-3-25 14:53:18 | 只看該作者
The Possible Forms of Edgeworth Expansions for Asymptotically Efficient Estimator-Sequences,Chapter 8 contains asymptotic bounds for the concentration of estimator-sequences for real-valued functionals: Section 8.2 for as. median unbiased estimator-sequences, Section 8.3 for estimator-sequences the distributions of which admit a certain as. expansion.
24#
發(fā)表于 2025-3-25 17:49:54 | 只看該作者
25#
發(fā)表于 2025-3-25 20:36:50 | 只看該作者
26#
發(fā)表于 2025-3-26 01:21:35 | 只看該作者
Lemmas,.. . (., .) . Y . f: x×y → ? .
27#
發(fā)表于 2025-3-26 05:02:36 | 只看該作者
https://doi.org/10.1007/978-1-4615-6479-9approximation; behavior; construction; distribution; estimator; function; functional; functions; Mathematica
28#
發(fā)表于 2025-3-26 11:23:50 | 只看該作者
29#
發(fā)表于 2025-3-26 13:41:40 | 只看該作者
https://doi.org/10.1007/978-1-4842-0749-9 suggest to describe the local structure of a general family β of probability measures by its tangent space, and the local behavior of a functional κ:β→?. by its gradient. Starting from these basic concepts, asymptotic envelope power functions for tests and asymptotic bounds for the concentration of
30#
發(fā)表于 2025-3-26 18:22:42 | 只看該作者
https://doi.org/10.1007/978-1-4615-3172-2tic log(.) are most powerful for . against .. In this section it will be shown that sequences of test statistics log(.), n ∈ ?, are most powerful of order o(n.) under relatively weak conditions on the remainder sequence R., n ∈ ?.
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