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Books on the topic 'Statistical Symmetries'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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1

Keating, Jonathan P. Discrete symmetries and spectral statistics. Hewlett Packard, 1996.

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2

Brunner, Lawrence J. Bayesian linear regression with error terms that have symmetric unimodal densities. Department of Statistics, University of Toronto, 1989.

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3

Cai, Jianqing. Statistical inference of the eigenspace components of a symmetric random deformation tensor. Verlag der Bayerischen Akademie der Wissenschaften in Kommission beim Verlags C.H. Beck, 2004.

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4

Hiroshi, Yadohisa, ed. Data analysis of asymmetric structures: Advanced approaches in computational statistics. Marcel Dekker, 2005.

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5

G, Genton Marc, ed. Skew-elliptical distributions and their applications: A journey beyond normality. Chapman & Hall/CRC Press, 2004.

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6

Symmetries in Quantum Mechanics and Statistical Physics. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-2478-8.

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7

Georg, Junker. Symmetries in Quantum Mechanics and Statistical Physics. Mdpi AG, 2021.

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8

Probabilistic Symmetries and Invariance Principles (Probability and Its Applications). Springer, 2006.

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9

Kachelriess, Michael. Thermal field theory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198802877.003.0015.

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After a review of the calculational approaches, the free energy of scalar particles in thermal equilibrium is calculated. The IR behaviour of mass-less scalar fields is examined, finding that a resummation of IR divergent terms is necessary. In general, particles acquire a temperature-dependent (Debye) mass, while symmetries of the Lagrangian may be hidden at low temperatures. In an appendix, the basics of equilibrium statistical physics is reviewe
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10

Marseken, Susan F., Miriam T. Timpledon, and Lambert M. Surhone, eds. Ring of Symmetric Functions: Algebra, Algebraic Combinatorics, Symmetric Polynomial, Representation Theory of the Symmetric Group, Polynomial Ring, Elementary Symmetric Polynomial, Newton's Identities. Betascript Publishers, 2010.

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11

Ionin, Yury J., and Mohan S. Shrikhande. Combinatorics of Symmetric Designs. Cambridge University Press, 2006.

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12

Ionin, Yury J., and Mohan S. Shrikhande. Combinatorics of Symmetric Designs. Cambridge University Press, 2006.

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13

Ionin, Yury J., and Mohan S. Shrikhande. Combinatorics of Symmetric Designs. Cambridge University Press, 2006.

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14

Ionin, Yury J., and Mohan S. Shrikhande. Combinatorics of Symmetric Designs. Cambridge University Press, 2010.

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15

Symmetric Multivariate and Related Distributions. Taylor & Francis Group, 2017.

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16

Fang, Kai Wang. Symmetric Multivariate and Related Distributions. Taylor & Francis Group, 2018.

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17

Fang, Kai Wang. Symmetric Multivariate and Related Distributions. Taylor & Francis Group, 2018.

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18

Fang, Kai Wang. Symmetric Multivariate and Related Distributions. Taylor & Francis Group, 2018.

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19

Rempala, Grzegorz, and Jacek Wesolowski. Symmetric Functionals on Random Matrices and Random Matchings Problems. Springer, 2010.

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20

Symmetric Functionals on Random Matrices and Random Matchings Problems (The IMA Volumes in Mathematics and its Applications Book 147). Springer, 2007.

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21

Ionin, Yury J., and Mohan S. Shrikhande. Combinatorics of Symmetric Designs (New Mathematical Monographs). Cambridge University Press, 2006.

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22

Saito, Takayuki, and Hiroshi Yadohisa. Data Analysis of Asymmetric Structures: Advanced Approaches in Computational Statistics. Taylor & Francis Group, 2004.

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23

Saito, Takayuki, and Hiroshi Yadohisa. Data Analysis of Asymmetric Structures: Advanced Approaches in Computational Statistics. Taylor & Francis Group, 2004.

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24

Saito, Takayuki, and Hiroshi Yadohisa. Data Analysis of Asymmetric Structures. Taylor & Francis Group, 2019.

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25

National Aeronautics and Space Administration (NASA) Staff. Shed Vortex Structure and Phase-Averaged Velocity Statistics in Symmetric/Asymmetric Turbulent Flat Plate Wakes. Independently Published, 2019.

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26

Cheng, Russell. The Pearson and Johnson Systems. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0009.

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This chapter re-examines two of the best-known systems of parametric distributions: the Pearson and the Johnson. It is shown that, in the Pearson system, Pearson Types III and V are boundary embedded models of the main Types I, IV, and VI. A comprehensive way of finding the best type to fit is given using appropriate score statistics to guide a systematic search of all model types, including symmetric boundary models. Maximum likelihood estimation is used and details of its numerical implementation are given. Type IV can be a difficult model to fit. A method is discussed for this model that is
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27

Kravtsov, Vladimir. Heavy-tailed random matrices. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.13.

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This article considers non-Gaussian random matrices consisting of random variables with heavy-tailed probability distributions. In probability theory heavy tails of distributions describe rare but violent events which usually have a dominant influence on the statistics. Furthermore, they completely change the universal properties of eigenvalues and eigenvectors of random matrices. This article focuses on the universal macroscopic properties of Wigner matrices belonging to the Lévy basin of attraction, matrices representing stable free random variables, and a class of heavy-tailed matrices obta
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28

Antognazza, Maria Rosa, ed. The Oxford Handbook of Leibniz. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199744725.001.0001.

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The extraordinary breadth and depth of Leibniz’s intellectual vision commands ever increasing attention. As more texts gradually emerge from seemingly bottomless archives, new facets of his contribution to an astonishing variety of fields come to light. This volume provides a uniquely comprehensive, systematic, and up-to-date appraisal of Leibniz’s thought thematically organized around its diverse but interrelated aspects. Discussion of his philosophical system naturally takes place of pride. A cluster of original essays revisit his logic, metaphysics, epistemology, philosophy of nature, moral
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29

Genton, Marc G. Skew-Elliptical Distributions and Their Applications: A Journey Beyond Normality. Taylor & Francis Group, 2004.

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30

Genton, Marc G. Skew-Elliptical Distributions and Their Applications: A Journey Beyond Normality. Taylor & Francis Group, 2004.

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31

Genton, Marc G. Skew-Elliptical Distributions and Their Applications: A Journey Beyond Normality. Taylor & Francis Group, 2004.

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32

Genton, Marc G. Skew-Elliptical Distributions and Their Applications: A Journey Beyond Normality. Taylor & Francis Group, 2004.

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33

Genton, Marc G. Skew-Elliptical Distributions and Their Applications: A Journey Beyond Normality. Taylor & Francis Group, 2004.

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