標(biāo)題: Titlebook: Asymptotic Optimal Inference for Non-ergodic Models; Ishwar V. Basawa,David John Scott Book 1983 Springer-Verlag New York Inc. 1983 Branch [打印本頁(yè)] 作者: proptosis 時(shí)間: 2025-3-21 17:53
書目名稱Asymptotic Optimal Inference for Non-ergodic Models影響因子(影響力)
書目名稱Asymptotic Optimal Inference for Non-ergodic Models影響因子(影響力)學(xué)科排名
書目名稱Asymptotic Optimal Inference for Non-ergodic Models網(wǎng)絡(luò)公開(kāi)度
書目名稱Asymptotic Optimal Inference for Non-ergodic Models網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Asymptotic Optimal Inference for Non-ergodic Models被引頻次
書目名稱Asymptotic Optimal Inference for Non-ergodic Models被引頻次學(xué)科排名
書目名稱Asymptotic Optimal Inference for Non-ergodic Models年度引用
書目名稱Asymptotic Optimal Inference for Non-ergodic Models年度引用學(xué)科排名
書目名稱Asymptotic Optimal Inference for Non-ergodic Models讀者反饋
書目名稱Asymptotic Optimal Inference for Non-ergodic Models讀者反饋學(xué)科排名
作者: Mirage 時(shí)間: 2025-3-21 21:47
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作者: abreast 時(shí)間: 2025-3-22 01:26
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作者: 自負(fù)的人 時(shí)間: 2025-3-22 05:09 作者: Coronation 時(shí)間: 2025-3-22 10:44 作者: 灰姑娘 時(shí)間: 2025-3-22 13:00
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作者: Verify 時(shí)間: 2025-3-22 18:18 作者: 劇本 時(shí)間: 2025-3-23 00:32
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.作者: archaeology 時(shí)間: 2025-3-23 03:08
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作者: Euphonious 時(shí)間: 2025-3-23 09:01
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.作者: 過(guò)份 時(shí)間: 2025-3-23 10:08
Optimal Asymptotic Tests,nditions 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.作者: Mingle 時(shí)間: 2025-3-23 16:15
https://doi.org/10.1007/978-1-4612-5505-5Branching process; Estimator; Likelihood; Random variable; diffusion process; statistics作者: backdrop 時(shí)間: 2025-3-23 19:30
978-0-387-90810-6Springer-Verlag New York Inc. 1983作者: Immunoglobulin 時(shí)間: 2025-3-23 23:24
https://doi.org/10.1007/978-3-319-51777-3This chapter is concerned with the formulation of a model which generalises the classical Fisher-Rao-Le Cam model as previewed in Chapter 0, and a discussion of an asymptotic model which approximates the proposed general model.作者: ADORN 時(shí)間: 2025-3-24 04:05 作者: 媽媽不開(kāi)心 時(shí)間: 2025-3-24 10:12 作者: 甜得發(fā)膩 時(shí)間: 2025-3-24 13:54 作者: Dri727 時(shí)間: 2025-3-24 15:19
Classical physics on a finite phase spaceich 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作者: Asparagus 時(shí)間: 2025-3-24 19:39 作者: FLINT 時(shí)間: 2025-3-24 23:38 作者: 不近人情 時(shí)間: 2025-3-25 07:09 作者: 逗它小傻瓜 時(shí)間: 2025-3-25 11:25 作者: 他去就結(jié)束 時(shí)間: 2025-3-25 15:27
Charles E. Burkhardt,Jacob J. Leventhalse models of non-ergodic type (see §2 for definitions), and results on efficiency of estimators and tests will be discussed using a unified approach. Our aim in this chapter is to present the main ideas and general asymptotic results in an informal manner. More detailed treatment of specific problems discussed here is given in subsequent chapters.作者: conifer 時(shí)間: 2025-3-25 15:52
https://doi.org/10.1007/978-1-4615-6205-4f a general non-ergodic model defined in terras of the non-local asymptotic behaviour of the log-likelihood ratio and discuss various applications. Also, extensions of Bahadur efficiency concepts to such models will be briefly indicated.作者: 裹住 時(shí)間: 2025-3-25 20:56 作者: entice 時(shí)間: 2025-3-26 03:16 作者: Valves 時(shí)間: 2025-3-26 04:24 作者: BARB 時(shí)間: 2025-3-26 09:58
Efficiency of Estimation,timators, there is an upper bound for the asymptotic concentration, such that the set of parameter values on which any particular estimator has higher concentration is of Lebesgue measure zero. The restriction placed on the class of competing estimators in order to assert the validity of the upper b作者: 才能 時(shí)間: 2025-3-26 13:03 作者: 迅速飛過(guò) 時(shí)間: 2025-3-26 20:42 作者: Hyperopia 時(shí)間: 2025-3-26 23:11 作者: 歹徒 時(shí)間: 2025-3-27 01:46
9樓作者: Visual-Field 時(shí)間: 2025-3-27 07:25
10樓作者: Graduated 時(shí)間: 2025-3-27 10:38
10樓作者: Prostatism 時(shí)間: 2025-3-27 15:38
10樓作者: 不可知論 時(shí)間: 2025-3-27 19:54
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