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Titre : Elements of the theory of Markov processes and their applications Type de document : texte imprimé Auteurs : A. T. Bharucha Reid (1927-1985), Auteur Editeur : New York ; Toronto ; Paris ; London [International] : McGraw Hill Année de publication : cop. 1960 Collection : McGraw-Hill series in probability and statistics Importance : XI-468 p. Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : PPN 015236919 Langues : Anglais (eng) Tags : Markov, Processus de Processus stochastiques Probabilités Statistique mathématique Markov processes Stochastic processes Probabilities Mathematical statistics Index. décimale : 519.23 Processus probabilistes - Processus stochastiques - Processus gaussiens Note de contenu : Notes bibliogr. Index Elements of the theory of Markov processes and their applications [texte imprimé] / A. T. Bharucha Reid (1927-1985), Auteur . - New York ; Toronto ; Paris ; London (International) : McGraw Hill, cop. 1960 . - XI-468 p. : ill. ; 24 cm. - (McGraw-Hill series in probability and statistics) .
ISSN : PPN 015236919
Langues : Anglais (eng)
Tags : Markov, Processus de Processus stochastiques Probabilités Statistique mathématique Markov processes Stochastic processes Probabilities Mathematical statistics Index. décimale : 519.23 Processus probabilistes - Processus stochastiques - Processus gaussiens Note de contenu : Notes bibliogr. Index Réservation
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Code-barres Cote Support Localisation Section Disponibilité Nom du donateur OCA-VV-000450 F4-450 Ouvrages / Books OCA Bib. Lagrange Nice Valrose VV-F3/F4-Statistiques et Probabilités Disponible
Titre : Gaussian Processes for Machine Learning Type de document : texte imprimé Auteurs : Carl Edward Rasmussen (1969-....), Auteur ; Christopher K. I. Williams, Auteur Editeur : Cambridge, Mass. : MIT Press Année de publication : 2006, cop. 2006 Collection : Adaptive computation and machine learning Importance : 1 vol. (XVIII-248 p.) Présentation : graphiques, figures, illustrations, jaquette illustrée Format : 26 cm ISBN/ISSN/EAN : 978-0-262-18253-9 Note générale : PPN 097588938 .- ISBN 0-262-18253-X (rel.) Document accessible en ligne sur Mit Press direct (https://direct.mit.edu/books/oa-monograph/2320/Gaussian-Processes-for-Machine-Learning ; https://gaussianprocess.org/gpml/chapters/RW.pdf) Langues : Anglais (eng) Tags : Processus gaussiens -- Informatique Apprentissage automatique -- Modèles mathématiques Markov, Processus de Gaussian processes -- Data processing Machine learning -- Mathematical models Markov processes Index. décimale : 519.23 Processus probabilistes - Processus stochastiques - Processus gaussiens Résumé : Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes. Note de contenu : Bibliographie p. [223]-238. Index auteurs p.[239]-243. Index sujet p.[244]-248 En ligne : https://direct.mit.edu/books/oa-monograph/2320/Gaussian-Processes-for-Machine-Le [...] Gaussian Processes for Machine Learning [texte imprimé] / Carl Edward Rasmussen (1969-....), Auteur ; Christopher K. I. Williams, Auteur . - Cambridge, Mass. : MIT Press, 2006, cop. 2006 . - 1 vol. (XVIII-248 p.) : graphiques, figures, illustrations, jaquette illustrée ; 26 cm. - (Adaptive computation and machine learning) .
ISBN : 978-0-262-18253-9
PPN 097588938 .- ISBN 0-262-18253-X (rel.) Document accessible en ligne sur Mit Press direct (https://direct.mit.edu/books/oa-monograph/2320/Gaussian-Processes-for-Machine-Learning ; https://gaussianprocess.org/gpml/chapters/RW.pdf)
Langues : Anglais (eng)
Tags : Processus gaussiens -- Informatique Apprentissage automatique -- Modèles mathématiques Markov, Processus de Gaussian processes -- Data processing Machine learning -- Mathematical models Markov processes Index. décimale : 519.23 Processus probabilistes - Processus stochastiques - Processus gaussiens Résumé : Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes. Note de contenu : Bibliographie p. [223]-238. Index auteurs p.[239]-243. Index sujet p.[244]-248 En ligne : https://direct.mit.edu/books/oa-monograph/2320/Gaussian-Processes-for-Machine-Le [...] Réservation
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Code-barres Cote Support Localisation Section Disponibilité Nom du donateur OCA-NI-011187 011187 Ouvrages / Books OCA Bib. Nice Mont-Gros NI-Salle de lecture-Ouvrages Sorti jusqu'au 09/04/2026
Titre : Stochastic processes in physics and chemistry [3rd ed.] Type de document : texte imprimé Auteurs : N. G. Van Kampen (1921-....), Auteur Mention d'édition : Third Edition Editeur : Amsterdam ; Oxford ; New York : North Holland Publishers Année de publication : 2007, cop. 2007 Collection : North Holland personal library, ISSN 0925-5818 Importance : 1 vol. (XVI- 463 p.) Présentation : ill. en noir et blanc Format : 23 cm ISBN/ISSN/EAN : 978-0-444-52965-7 Note générale : PPN 115389903 Langues : Anglais (eng) Tags : Physique -- Méthodes statistiques Chimie -- Méthodes statistiques Processus stochastiques Variables aléatoires Markov, Processus de Fokker-Planck, Équation de Physics -- Statistical methods Chemistry -- Statistical methods Stochastic processes Random variables Markov processes Fokker-Planck equation Index. décimale : 519.23 Processus probabilistes - Processus stochastiques - Processus gaussiens Résumé : This new edition of Van Kampen's standard work has been completely revised and updated. Three major changes have also been made. The Langevin equation receives more attention in a separate chapter in which non-Gaussian and colored noise are introduced. Another additional chapter contains old and new material on first-passage times and related subjects which lay the foundation for the chapter on unstable systems. Finally a completely new chapter has been written on the quantum mechanical foundations of noise. The references have also been expanded and updated. Note de contenu : Notes bibliogr. - Index Sujets (p. 457-463) Stochastic processes in physics and chemistry [3rd ed.] [texte imprimé] / N. G. Van Kampen (1921-....), Auteur . - Third Edition . - Amsterdam ; Oxford ; New York : North Holland Publishers, 2007, cop. 2007 . - 1 vol. (XVI- 463 p.) : ill. en noir et blanc ; 23 cm. - (North Holland personal library, ISSN 0925-5818) .
ISBN : 978-0-444-52965-7
PPN 115389903
Langues : Anglais (eng)
Tags : Physique -- Méthodes statistiques Chimie -- Méthodes statistiques Processus stochastiques Variables aléatoires Markov, Processus de Fokker-Planck, Équation de Physics -- Statistical methods Chemistry -- Statistical methods Stochastic processes Random variables Markov processes Fokker-Planck equation Index. décimale : 519.23 Processus probabilistes - Processus stochastiques - Processus gaussiens Résumé : This new edition of Van Kampen's standard work has been completely revised and updated. Three major changes have also been made. The Langevin equation receives more attention in a separate chapter in which non-Gaussian and colored noise are introduced. Another additional chapter contains old and new material on first-passage times and related subjects which lay the foundation for the chapter on unstable systems. Finally a completely new chapter has been written on the quantum mechanical foundations of noise. The references have also been expanded and updated. Note de contenu : Notes bibliogr. - Index Sujets (p. 457-463) Réservation
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Code-barres Cote Support Localisation Section Disponibilité Nom du donateur OCA-NI-010936 010936 Ouvrages / Books OCA Bib. Nice Mont-Gros NI-Salle de lecture-Ouvrages Sorti jusqu'au 25/01/2026 Réservation
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Code-barres Cote Support Localisation Section Disponibilité Nom du donateur OCA-NI-003786 003786 Ouvrages / Books OCA Bib. Nice Mont-Gros NI-Salle de lecture-Ouvrages Disponible Statistical analysis of spatial and spatio-temporal point patterns [3rd ed.] / Peter J. Diggle (2014, cop. 2014)
Titre : Statistical analysis of spatial and spatio-temporal point patterns [3rd ed.] Type de document : texte imprimé Auteurs : Peter J. Diggle, Auteur Mention d'édition : Third Edition Editeur : Boca Raton ; London ; New York : CRC Press Année de publication : 2014, cop. 2014 Collection : Monographs on statistics and applied probability num. 128 Importance : 1 vol. (XXXI-267 p.) Présentation : ill., couv. ill. en coul. Format : 24 cm ISBN/ISSN/EAN : 978-1-4665-6023-9 Note générale : To the memory of Julian Besag FRS, 1945-2010. -- PPN 19546768X Langues : Anglais (eng) Tags : Analyse spatiale (Statistique) R (logiciel) Processus stochastiques Markov, Processus de Poisson, Processus de Epidémiologie Évaluation du risque -- Méthodes statistiques Spatial analysis (Statistics) Stochastic processes Markov processes Poisson processes Epidemiology Risk assessment Index. décimale : 519.53 Statistiques descriptives, analyse multivariée, analyse de la variance et de la covariance Résumé : Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author's website -- Source other than Library of Congress Note de contenu : Sommaire (abrégé) : List of figures (p.xv). - List of tables (p.xxvii). - Preface (p.xxix). - 1. Introduction (p.1). - 2. Preliminary testing (p.17). - 3. Methods for sparsely sampled patterns (p.39). - 4. Spatial point processes (p.55). - 5. Nonparametric methods (p.83) - 6. Models (p.99) - 7. Model-fitting using summary descriptions (p.131). - 8. Model-fitting using likelihood-based methods (p.151) - 9. Point process methods in spatial epidemiology (p.173). - 10. Spatio-temporal point processes (p.195). - 11. Exploratory analysis (p.209). - 12. Empirical models and methods (p.223). - 13. Mechanistic models and methods (p.235). - References (p.245) - Index (p.263)
Statistical analysis of spatial and spatio-temporal point patterns [3rd ed.] [texte imprimé] / Peter J. Diggle, Auteur . - Third Edition . - Boca Raton ; London ; New York : CRC Press, 2014, cop. 2014 . - 1 vol. (XXXI-267 p.) : ill., couv. ill. en coul. ; 24 cm. - (Monographs on statistics and applied probability; 128) .
ISBN : 978-1-4665-6023-9
To the memory of Julian Besag FRS, 1945-2010. -- PPN 19546768X
Langues : Anglais (eng)
Tags : Analyse spatiale (Statistique) R (logiciel) Processus stochastiques Markov, Processus de Poisson, Processus de Epidémiologie Évaluation du risque -- Méthodes statistiques Spatial analysis (Statistics) Stochastic processes Markov processes Poisson processes Epidemiology Risk assessment Index. décimale : 519.53 Statistiques descriptives, analyse multivariée, analyse de la variance et de la covariance Résumé : Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author's website -- Source other than Library of Congress Note de contenu : Sommaire (abrégé) : List of figures (p.xv). - List of tables (p.xxvii). - Preface (p.xxix). - 1. Introduction (p.1). - 2. Preliminary testing (p.17). - 3. Methods for sparsely sampled patterns (p.39). - 4. Spatial point processes (p.55). - 5. Nonparametric methods (p.83) - 6. Models (p.99) - 7. Model-fitting using summary descriptions (p.131). - 8. Model-fitting using likelihood-based methods (p.151) - 9. Point process methods in spatial epidemiology (p.173). - 10. Spatio-temporal point processes (p.195). - 11. Exploratory analysis (p.209). - 12. Empirical models and methods (p.223). - 13. Mechanistic models and methods (p.235). - References (p.245) - Index (p.263)
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Code-barres Cote Support Localisation Section Disponibilité Nom du donateur OCA-VV-002121 F3-2121 Ouvrages / Books OCA Bib. Lagrange Nice Valrose VV-F3/F4-Statistiques et Probabilités Sorti jusqu'au 17/03/2026
