Titlebook: Geometric Modeling in Probability and Statistics; Ovidiu Calin,Constantin Udrişte Textbook 2014 Springer International Publishing Switzerl

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书目名称Geometric Modeling in Probability and Statistics影响因子(影响力)




书目名称Geometric Modeling in Probability and Statistics影响因子(影响力)学科排名




书目名称Geometric Modeling in Probability and Statistics网络公开度




书目名称Geometric Modeling in Probability and Statistics网络公开度学科排名




书目名称Geometric Modeling in Probability and Statistics被引频次




书目名称Geometric Modeling in Probability and Statistics被引频次学科排名




书目名称Geometric Modeling in Probability and Statistics年度引用




书目名称Geometric Modeling in Probability and Statistics年度引用学科排名




书目名称Geometric Modeling in Probability and Statistics读者反馈




书目名称Geometric Modeling in Probability and Statistics读者反馈学科排名

probate

Textbook 2014accompanied by software that is able to. .provide numerical computations of several information geometric objects. The reader will understand a flourishing field of mathematics in which very few books have been written so far..

Optic-Disk

https://doi.org/10.1007/978-3-476-03356-7ack can be corrected by introducing another concept, which measures the relative entropy between two given densities. This chapter studies the Kullback–Leibler relative entropy (known also as the Kullback–Leibler divergence) between two probability densities in both discrete and continuous cases.

远足

https://doi.org/10.1007/978-3-663-04759-9of mean, variance, or any . moments. The solution of these variational problems belongs to the exponential family. However, explicit solutions exist only in a few particular cases. A distinguished role is played by the study of the Maxwell–Boltzmann distribution.

BOGUS

Métabolisme et fonctions rénalestiable manifolds, tangent space, vector fields, differentiable maps, 1-forms, tensors, linear connections, Riemannian manifolds, and the Levi–Civita connection. The material of this chapter forms the basis for next chapters.

新义

新义

overrule

时间等

https://doi.org/10.1007/978-3-031-69698-5 the first and second fundamental forms, curvatures, mean curvatures, and the relations among them..This material adapts the well-known theory of submanifolds to the statistical manifolds framework and consists mainly in the contributions of the authors.

insert

Kullback–Leibler Relative Entropyack can be corrected by introducing another concept, which measures the relative entropy between two given densities. This chapter studies the Kullback–Leibler relative entropy (known also as the Kullback–Leibler divergence) between two probability densities in both discrete and continuous cases.