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Books on the topic 'Geometrical Probability'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Djang, Fred C. Applications of geometrical probability. Consortium for Mathematics and Its Applications, Inc. (COMAP), 1988.

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2

Djang, Fred C. Applications of geometrical probability. COMAR, 1988.

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3

Klain, Daniel A. Introduction to geometric probability. Cambridge University Press, 1997.

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4

Avram, Florin. On central limit theorems in geometrical probability. Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1991.

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5

Mathai, A. M. An introduction to geometrical probability: Distributional aspects with applications. Gordon & Breach, 1999.

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6

Fernique, Xavier, Bernard Heinkel, Paul-André Meyer, and Michael B. Marcus, eds. Geometrical and Statistical Aspects of Probability in Banach Spaces. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/bfb0077094.

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7

Ghandehari, Mostafa. Tennis, geometric progression, probability and basketball. University of Texas at Arlington, Dept. of Mathematics, 1999.

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8

Ambartzumian, R. V. Factorization calculus and geometric probability. Cambridge University Press, 1990.

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9

Integral geometry and geometric probability. 2nd ed. Cambridge University Press, 2004.

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10

Kalashnikov, Vladimir Vi͡acheslavovich. Geometric sums, bounds for rare events with applications: Risk analysis, reliability, queueing. Kluwer Academic, 1997.

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11

Limit theorems for unions of random closed sets. Springer-Verlag, 1993.

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12

Bobkov, Serguei G. Some connections between isoperimetric and Sobolev-type inequalities. American Mathematical Society, 1997.

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13

Convegno italiano di geometria integrale, probabilità geometriche e corpi convessi (5th 1995 Milan, Italy). V Convegno italiano di geometria integrale, probabilità geometriche e corpi convessi: Milano, 19-22 aprile 1995. Sede della società, 1996.

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14

Convegno, italiano di geometria integrale probabilità geometriche e. corpi convessi (4th 1994 Bari Italy). IV Convegno italiano di geometria integrale, probabilità geometriche e corpi convessi: Bari, 2-5 maggio 1994. Sede della società, 1995.

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15

Mariusz, Urbaʹnski, ed. Graph directed Markov systems: Geometry and dynamics of limit sets. Cambridge University Press, 2003.

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16

author, Giannopoulos Apostolos 1963, Valettas Petros 1982 author, and Vritsiou Beatrice-Helen author, eds. Geometry of isotropic convex bodies. American Mathematical Society, 2014.

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17

Stanford Symposium on Algebraic Topology: Applications and New Directions (2012 : Stanford, Calif.), ed. Algebraic topology: Applications and new directions : Stanford Symposium on Algebraic Topology: Applications and New Directions, July 23--27, 2012, Stanford University, Stanford, CA. American Mathematical Society, 2014.

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18

1963-, Giannopoulos Apostolos, and Milman Vitali D. 1939-, eds. Asymptotic geometric analysis. American Mathematical Society, 2015.

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19

Jakobson, Dmitry, Pierre Albin, and Frédéric Rochon. Geometric and spectral analysis. American Mathematical Society, 2014.

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20

1968-, Dafni Galia Devora, McCann Robert John 1968-, and Stancu Alina 1968-, eds. Analysis and geometry of metric measure spaces: Lecture notes of the 50th Séminaire de Mathématiques Supérieures (SMS), Montréal, 2011. American Mathematical Society, 2013.

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21

Concentration, functional inequalities, and isoperimetry: International workshop, October 29-November 1, 2009, Florida Atlantic University, Boca Raton, Florida. American Mathematical Society, 2011.

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22

Koli︠a︡da, S. F. Dynamics and numbers: A special program, June 1-July 31, 2014, Max Planck Institute for Mathematics, Bonn, Germany : international conference, July 21-25, 2014, Max Planck Institute for Mathematics, Bonn, Germany. Edited by Max-Planck-Institut für Mathematik. American Mathematical Society, 2016.

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23

Simon, Barry. Advanced complex analysis. American Mathematical Society, 2015.

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24

Calin, Ovidiu, and Constantin Udrişte. Geometric Modeling in Probability and Statistics. Springer, 2016.

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25

Geometric Modeling in Probability and Statistics. Springer, 2014.

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26

Zheng, Youlu. Computational aspects of some packing and covering problems in geometrical probability. 1987.

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27

Mathai, A. M. An Introduction to Geometrical Probability: Distributional Aspects with Applications (Statistical Distributions & Models with Applications). CRC, 1999.

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28

Meyer, Paul-Andre, Xavier Fernique, Bernard Heinkel, and Michel B. Marcus. Geometrical and Statistical Aspects of Probability in Banach Spaces: Actes des Journées SMF de Calcul des Probabilités dans les Espaces de Banach, ... 20 juin 1985. Springer, 1986.

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29

1934-, Fernique X. M., and Société mathématique de France, eds. Geometrical and statistical aspects of probability in Banach spaces: Actes des Journees SMF de calcul des probabilites dans les espaces de Banach, organisees a Strasbourg les 19 et 20 juin 1985. Springer-Verlag, 1986.

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30

Probability and Analysis. Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 1986.

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31

Flewelling, Gary. Math activities using LogoWriter: Probability and statistics. International Society for Technology in Education, 1994.

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32

Dietrich, Franz, and Christian List. Probabilistic Opinion Pooling. Edited by Alan Hájek and Christopher Hitchcock. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199607617.013.37.

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Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This chapter is a review of several proposed solutions to this problem, focusing on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). Axiomatic characterizations of e

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33

V, Buldygin V., and Kharazishvili A. B, eds. Geometric aspects of probability theory and mathematical statistics. Kluwer Academic, 2000.

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34

Letta, G. Probability and Analysis: Lectures Given at the 1st 1985 Session of the Centro Internazionale Matematico Estivo (Lecture Notes in Mathematics). Springer, 1986.

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35

G, Letta, Pratelli M, and Centro internazionale matematico estivo, eds. Probability and analysis: Lectures given at the 1st 1985 session of the Centro internazionale matematico estivo (C.I.M.E.) held at Varenna, Como, Italy, May 31-June 8, 1985. Springer-Verlag, 1986.

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36

Kharazishvili, A. B., and V. V. Buldygin. Geometric Aspects of Probability Theory and Mathematical Statistics (MATHEMATICS AND ITS APPLICATIONS Volume 514) (Mathematics and Its Applications). Springer, 2000.

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37

Grenander, Ulf, and Michael I. Miller. Pattern Theory. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780198505709.001.0001.

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Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computer science, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website. The book commences with a short ov

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38

Coolen, Ton, Alessia Annibale, and Ekaterina Roberts. Generating Random Networks and Graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.001.0001.

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This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation,

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