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標(biāo)題: Titlebook: Applications of Measure Theory to Statistics; Gogi Pantsulaia Book 2016 Springer International Publishing Switzerland 2016 NHST.Objective [打印本頁(yè)]

作者: Addiction    時(shí)間: 2025-3-21 17:39
書目名稱Applications of Measure Theory to Statistics影響因子(影響力)




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作者: 牲畜欄    時(shí)間: 2025-3-21 20:49
https://doi.org/10.1007/978-3-642-17182-6 which .. In the present chapter the same set is studied from the point of view of shyness and it is demonstrated that it is shy in .. In the Solovay model, the structure of the set of all sequences uniformly distributed modulo 1 in . is studied from the point of view of shyness and it is shown that
作者: 斑駁    時(shí)間: 2025-3-22 02:56
Was ich gerne weitergeben m?chtemeasures and infinite powers of Borel diffused probability measures on .. More precisely, there is given Yamasaki’s proof that no infinite power of the Borel probability measure with a strictly positive density function on . has an equivalent Moore–Yamasaki–Kharazishvili type measure. A certain modi
作者: 為敵    時(shí)間: 2025-3-22 07:11
https://doi.org/10.1007/978-3-658-42084-0ng objective and strong objective estimates of unknown parameters are introduced in a Polish nonlocally compact group admitting an invariant metric and relations between them are studied in this chapter. An example of a weakly separated statistical structure is constructed for which a question askin
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作者: Accessible    時(shí)間: 2025-3-22 21:17
Gogi PantsulaiaHelps the reader to understand some conjectures arising in the criticism of null hypothesis significance testing (NHST).Includes a special chapter that helps the reader to calculate infinite-dimension
作者: FLAX    時(shí)間: 2025-3-23 02:47
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https://doi.org/10.1007/978-3-319-45578-5NHST; Objective estimations of an unknown parameter; Harr null set; Haar ambivalent set; Measure Thoery;
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Calculation of Improper Integrals by Using Uniformly Distributed Sequences,o a maximal set of uniformly distributed sequences in (0,?1) that strictly contains the set of all sequences having the form . for some irrational number . and having the full .-measure, where . denotes the infinite power of the linear Lebesgue measure . in (0,?1).
作者: Conjuction    時(shí)間: 2025-3-24 14:12
Structure of All Real-Valued Sequences Uniformly Distributed in , from the Point of View of Shyness which .. In the present chapter the same set is studied from the point of view of shyness and it is demonstrated that it is shy in .. In the Solovay model, the structure of the set of all sequences uniformly distributed modulo 1 in . is studied from the point of view of shyness and it is shown that
作者: 倔強(qiáng)不能    時(shí)間: 2025-3-24 16:17
,On Moore–Yamasaki–Kharazishvili Type Measures and the Infinite Powers of Borel Diffused Probabilitymeasures and infinite powers of Borel diffused probability measures on .. More precisely, there is given Yamasaki’s proof that no infinite power of the Borel probability measure with a strictly positive density function on . has an equivalent Moore–Yamasaki–Kharazishvili type measure. A certain modi
作者: 大約冬季    時(shí)間: 2025-3-24 21:14
Objective and Strong Objective Consistent Estimates of Unknown Parameters for Statistical Structureng objective and strong objective estimates of unknown parameters are introduced in a Polish nonlocally compact group admitting an invariant metric and relations between them are studied in this chapter. An example of a weakly separated statistical structure is constructed for which a question askin
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作者: 固定某物    時(shí)間: 2025-3-26 06:48
Was ich gerne weitergeben m?chtestems, group theory, and descriptive set theory. In the present chapter their notion of “prevalence” is used in studying structures of domains of some infinite sample statistics and in explaining why null hypothesis is rejected for almost every infinite sample by the hypothesis testing of a maximal reliability.
作者: obsolete    時(shí)間: 2025-3-26 09:34
Why Null Hypothesis Is Rejected for Almost Every Infinite Sample by the Hypothesis Testing of a Maxstems, group theory, and descriptive set theory. In the present chapter their notion of “prevalence” is used in studying structures of domains of some infinite sample statistics and in explaining why null hypothesis is rejected for almost every infinite sample by the hypothesis testing of a maximal reliability.
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