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Livros sobre o tema "Geometrisk statistik"

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Autor: Grafiati

Publicado: 22 de junho de 2024

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1

Fang, Kʻai-tʻai. Number-theoretic methods in statistics. London: Chapman & Hall, 1994.

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2

Pawlowsky-Glahn, Vera. Modelling and analysis of compositional data. Chichester, West Sussex: John Wiley & Sons, Inc., 2015.

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3

Roux, Brigitte Le. Combinatorial Inference in Geometric Data Analysis. Boca Raton, Florida, USA: Chapman and Hall/CRC, Taylor & Francis Group, 2019.

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4

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

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5

Stoyan, Dietrich. Fractals, random shapes, and point fields: Methods of geometrical statistics. Chichester: Wiley, 1994.

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6

1911-, Ledermann Walter, e Vajda Steven 1901-, eds. Handbook of applicable mathematics. Chichester: Wiley, 1985.

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7

Stoyan, Dietrich. Stochastic geometry and its applications. Chichester [W. Sussex]: Wiley, 1987.

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8

Stoyan, Dietrich. Stochastic geometry and its applications. 2^a ed. Chichester: Wiley, 1995.

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9

Mauldin, R. Daniel. Graph directed Markov systems: Geometry and dynamics of limit sets. Cambridge: Cambridge University Press, 2003.

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10

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

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11

Roux, Brigitte Le, Solène Bienaise e Jean-Luc Durand. Combinatorial Inference in Geometric Data Analysis. Taylor & Francis Group, 2019.

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12

Roux, Brigitte Le, Solène Bienaise e Jean-Luc Durand. Combinatorial Inference in Geometric Data Analysis. Taylor & Francis Group, 2019.

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13

Kharazishvili, A. B., e V. V. Buldygin. Geometric Aspects of Probability Theory and Mathematical Statistics. Springer, 2013.

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14

Kharazishvili, A. B., e V. V. Buldygin. Geometric Aspects of Probability Theory and Mathematical Statistics. Springer London, Limited, 2010.

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15

Kanatani, Kenichi. Statistical Optimization for Geometric Computation: Theory and Practice. Dover Publications, 2005.

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16

Kanatani, Kenichi. Statistical Optimization for Geometric Computation: Theory and Practice. Dover Publications, Incorporated, 2011.

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17

Grenander, Ulf, e 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 overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometric transformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum. Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look at inference, exploring random sampling approaches for estimation of model order and parametric representing of shapes.

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18

Kharazishvili, A. B., e 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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19

Boots, Barry, Kokichi Sugihara, Sung Nok Chiu e Atsuyuki Okabe. Spatial Tessellations: Concepts and Applications of Voronoi Diagrams (Wiley Series in Probability and Statistics). 2^a ed. Wiley, 2000.

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20

Roux, Brigitte Le, Solène Bienaise e Jean-Luc Durand. Combinatorial Inference in Geometric Data Analysis. Taylor & Francis Group, 2019.

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21

Roux, Brigitte Le, Solène Bienaise e Jean-Luc Durand. Combinatorial Inference in Geometric Data Analysis. Taylor & Francis Group, 2021.

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22

Ledermann, Walter. Combinatorics and Geometry (Handbook of Applicable Mathematics). John Wiley & Sons Inc, 1985.

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23

Ledermann, Walter. Combinatorics and Geometry (Handbook of Applicable Mathematics). John Wiley & Sons Inc, 1985.

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24

Nguyen, Hung T. An Introduction to Random Sets. Chapman & Hall/CRC, 2006.

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25

Woyczynski, Wojbor A. Geometry and Martingales in Banach Spaces. Taylor & Francis Group, 2018.

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26

Woyczynski, Wojbor A. Geometry and Martingales in Banach Spaces. Taylor & Francis Group, 2018.

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27

Woyczynski, Wojbor A. Geometry and Martingales in Banach Spaces. Taylor & Francis Group, 2018.

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28

Woyczynski, Wojbor A. Geometry and Martingales in Banach Spaces. Taylor & Francis Group, 2018.

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29

Kendall, Wilfrid S., Joseph Mecke e Dietrich Stoyan. Stochastic Geometry and Its Applications, 2nd Edition. 2^a ed. Wiley, 1996.

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30

Mecke, Joseph, e Dietrich Stoyan. Stochastische Geometrie. de Gruyter GmbH, Walter, 2022.

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31

Mecke, Joseph, e Dietrich Stoyan. Stochastische Geometrie: Eine Einführung. de Gruyter GmbH, Walter, 2022.

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