使高兴 发表于 2025-3-26 21:15:28

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TAP 发表于 2025-3-27 03:50:11

Summary,We characterise the starting points of the present book in Sect. .. Its main results are summarised in Sect. .. Several questions that one would like to have answered but that remain open, are collected in Sect. ..

严厉批评 发表于 2025-3-27 06:06:12

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Presbycusis 发表于 2025-3-27 13:16:20

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不断的变动 发表于 2025-3-27 16:40:36

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改良 发表于 2025-3-27 19:16:26

https://doi.org/10.1007/978-3-030-34728-4 density discussed in Sect. .. Under a reparameterisation of the hypothesis, the uniform density generally changes into another one that is no longer uniform. If there were a distribution invariant under all transformations, it would be the universal ignorance prior. Such a distribution does not exi

mediocrity 发表于 2025-3-27 21:57:44

Human Development and Criminal Behavior. of a vector space. The transformations of event and parameter, introduced in Chap. ., are nonlinear. The probability distributions . and . are not elements of a vector space. Is it possible to define form invariance in terms of linear transformations of a vector space? This would give the possibil

perimenopause 发表于 2025-3-28 06:02:21

Human Development and Criminal Behaviorarticular without knowledge of the multiplication function. This is useful because the analysis of the symmetry group may be difficult. This is even of basic importance, because the formula allows one to generalise the definition of the prior . to cases where form invariance does not exist or is not

violate 发表于 2025-3-28 08:33:41

Jens Rasmussen,William B. Rouser vague. Science never reaches exact results. Mathematics provides proofs but it is devoid of reality. The present book shows in mathematical terms how to express uncertain experience in scientific statements.

collagenase 发表于 2025-3-28 10:41:29

https://doi.org/10.1007/978-1-4615-9230-3densities and functions are discussed in Sect. .. A symmetry argument can define the prior. This is described in Sects. . and .. Prior distributions are not necessarily proper. In Sect. ., we comment on improper distributions because it is unusual to admit any of them. In Sect. ., we discuss the information conveyed by a proper distribution.
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