proptosis
发表于 2025-3-21 17:53:14
书目名称Asymptotic Optimal Inference for Non-ergodic Models影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0163821<br><br> <br><br>书目名称Asymptotic Optimal Inference for Non-ergodic Models读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0163821<br><br> <br><br>
Mirage
发表于 2025-3-21 21:47:15
Efficiency of Estimation,ich attains the maximal possible concentration about the true value of the parameter. It is easy to show that such an estimator also has minimum mean square error, so the theory incorporates the classical notions of estimation efficiency. Of course it is not in general possible to obtain an estimato
abreast
发表于 2025-3-22 01:26:38
Optimal Asymptotic Tests,given in §2 of Chapter 1 and we assume the LAMN condition is satisfied. This general model is used in §§3 and 4. In later sections more restrictive conditions are required. It turns out that the usual statistics such as the Rao’s score statistic, the Neyman statistic, and the likelihood-ratio (LR) s
自负的人
发表于 2025-3-22 05:09:35
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Coronation
发表于 2025-3-22 10:44:40
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灰姑娘
发表于 2025-3-22 13:00:58
Book 1983models. The non-ergodic family of models can be viewed as an extension of the usual Fisher-Rao model for asymptotics, referred to here as an ergodic family. The main feature of a non-ergodic model is that the sample Fisher information, appropriately normed, converges to a non-degenerate random varia
Verify
发表于 2025-3-22 18:18:41
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剧本
发表于 2025-3-23 00:32:51
Mixture Experiments and Conditional Inference,rst stage of the experiment has been performed. We then have only X(n) as our sample and the information that the experiment on V has been performed. The conditionality principle will still be in force; we may treat v as an unknown nuisance parameter and use the density p. for inference about α.
archaeology
发表于 2025-3-23 03:08:20
0930-0325 n-ergodic models. The non-ergodic family of models can be viewed as an extension of the usual Fisher-Rao model for asymptotics, referred to here as an ergodic family. The main feature of a non-ergodic model is that the sample Fisher information, appropriately normed, converges to a non-degenerate ra
Euphonious
发表于 2025-3-23 09:01:57
Classical models of quantum mechanicsnditions are required. It turns out that the usual statistics such as the Rao’s score statistic, the Neyman statistic, and the likelihood-ratio (LR) statistic exhibit non-standard asymptotic behaviour in the non-ergodic case, as regards efficiency and limit distributions.