Inference in hidden Markov models / Olivier Cappé (2005)

Public ISBD Titre : Inference in hidden Markov models Type de document : livre Auteurs : Olivier Cappé, Auteur ; Eric Moulines, Auteur ; Tobias Rydén, Auteur Editeur : New York : Springer Année de publication : 2005 Collection : Springer series in statistics Importance : 652 p. ISBN/ISSN/EAN : 978-0-387-40264-2 Note générale : ISBN-10 : 0-387-40264-0; DOI:10.1007/0-387-28982-8 Langues : Anglais (eng) Mots-clés : ALGORITHME  Modèle  Méthode statistique Résumé : Le site éditeur indique : Hidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more. This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models. This volume will suit anybody with an interest in inference for stochastic processes, and it will be useful for researchers and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The algorithmic parts of the book do not require an advanced mathematical background, while the more theoretical parts require knowledge of probability theory at the measure-theoretical level. Inference in hidden Markov models [livre] / Olivier Cappé, Auteur ; Eric Moulines, Auteur ; Tobias Rydén, Auteur . - New York : Springer, 2005 . - 652 p.. - (Springer series in statistics) . ISBN : 978-0-387-40264-2 ISBN-10 : 0-387-40264-0; DOI:10.1007/0-387-28982-8 Langues : Anglais (eng) Mots-clés : ALGORITHME  Modèle  Méthode statistique Résumé : Le site éditeur indique : Hidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more. This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models. This volume will suit anybody with an interest in inference for stochastic processes, and it will be useful for researchers and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The algorithmic parts of the book do not require an advanced mathematical background, while the more theoretical parts require knowledge of probability theory at the measure-theoretical level.

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
67432	CAP_11_67432	Livre	Salle des ouvrages	11_Mathématiques	Disponible

Principal component analysis / Jolliffe, I.T. (2002)  

Public ISBD Titre : Principal component analysis Type de document : livre Auteurs : Jolliffe, I.T. Mention d'édition : 02 éd. Editeur : New York : Springer Année de publication : 2002 Collection : Springer series in statistics Importance : 487 p. ISBN/ISSN/EAN : 978-0-387-95442-4 Langues : Anglais (eng) Mots-clés : Data analysis  Principal components analysis  Statistical methods Résumé : Principal component analysis is central to the study of multivariate data. Although one of the earliest multivariate techniques it continues to be the subject of much research, ranging from new model- based approaches to algorithmic ideas from neural networks. It is extremely versatile with applications in many disciplines. The first edition of this book was the first comprehensive text written solely on principal component analysis. The second edition updates and substantially expands the original version, and is once again the definitive text on the subject. It includes core material, current research and a wide range of applications. Its length is nearly double that of the first edition. Researchers in statistics, or in other fields that use principal component analysis, will find that the book gives an authoritative yet accessible account of the subject. It is also a valuable resource for graduate courses in multivariate analysis. The book requires some knowledge of matrix algebra. Ian Jolliffe is Professor of Statistics at the University of Aberdeen. He is author or co-author of over 60 research papers and three other books. His research interests are broad, but aspects of principal component analysis have fascinated him and kept him busy for over 30 years. Note de contenu : Pbk; Voir aussi la 1ère édition de 1986 à la cote 67985/11 En ligne : http://www.loc.gov/catdir/enhancements/fy0817/2002019560-t.html Principal component analysis [livre] / Jolliffe, I.T.  . -  02 éd. . - New York : Springer, 2002 . - 487 p.. - (Springer series in statistics) . ISBN : 978-0-387-95442-4 Langues : Anglais (eng) Mots-clés : Data analysis  Principal components analysis  Statistical methods Résumé : Principal component analysis is central to the study of multivariate data. Although one of the earliest multivariate techniques it continues to be the subject of much research, ranging from new model- based approaches to algorithmic ideas from neural networks. It is extremely versatile with applications in many disciplines. The first edition of this book was the first comprehensive text written solely on principal component analysis. The second edition updates and substantially expands the original version, and is once again the definitive text on the subject. It includes core material, current research and a wide range of applications. Its length is nearly double that of the first edition. Researchers in statistics, or in other fields that use principal component analysis, will find that the book gives an authoritative yet accessible account of the subject. It is also a valuable resource for graduate courses in multivariate analysis. The book requires some knowledge of matrix algebra. Ian Jolliffe is Professor of Statistics at the University of Aberdeen. He is author or co-author of over 60 research papers and three other books. His research interests are broad, but aspects of principal component analysis have fascinated him and kept him busy for over 30 years. Note de contenu : Pbk; Voir aussi la 1ère édition de 1986 à la cote 67985/11 En ligne : http://www.loc.gov/catdir/enhancements/fy0817/2002019560-t.html

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
68494	Jol_11_68494	Livre	Salle des ouvrages	11_Mathématiques	Disponible

Linear models: least squares and alternatives / Rao, C.R. ; Toutenburg, H. (1999)

Public ISBD Titre : Linear models: least squares and alternatives Type de document : livre Auteurs : Rao, C.R. ; Toutenburg, H. Mention d'édition : 02 éd. Editeur : New York : Springer Année de publication : 1999 Collection : Springer series in statistics Importance : 427 p. ISBN/ISSN/EAN : 978-0-387-98848-1 Note générale : Inventaire 2007: Pointé en rayon Mots-clés : Algèbre  MATRIX  MODELE LINEAIRE  REGRESSION LINEAIRE Note de contenu : Hbk; Linear models: least squares and alternatives [livre] / Rao, C.R. ; Toutenburg, H.  . -  02 éd. . - New York : Springer, 1999 . - 427 p.. - (Springer series in statistics) . ISBN : 978-0-387-98848-1 Inventaire 2007: Pointé en rayon Mots-clés : Algèbre  MATRIX  MODELE LINEAIRE  REGRESSION LINEAIRE Note de contenu : Hbk;

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
65548	Rao_11_65548	Livre	Salle des ouvrages	11_Mathématiques	Disponible

Modern concepts and theorems of mathematical statistics / Manoukian, E.B. (1986)

Public ISBD Titre : Modern concepts and theorems of mathematical statistics Type de document : livre Auteurs : Manoukian, E.B. Editeur : New York : Springer Année de publication : 1986 Collection : Springer series in statistics Importance : 156 p. ISBN/ISSN/EAN : 978-0-387-96186-6 Note générale : Inventaire 2007: Pointé en rayon Mots-clés : CONCEPT  DISTRIBUTION STATISTIQUE  Mathématique  Statistique Note de contenu : Hbk; Modern concepts and theorems of mathematical statistics [livre] / Manoukian, E.B. . - New York : Springer, 1986 . - 156 p.. - (Springer series in statistics) . ISBN : 978-0-387-96186-6 Inventaire 2007: Pointé en rayon Mots-clés : CONCEPT  DISTRIBUTION STATISTIQUE  Mathématique  Statistique Note de contenu : Hbk;

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
52419	Man_11_52419	Livre	Salle des ouvrages	11_Mathématiques	Disponible

Principal component analysis / Jolliffe, I.T. (1986)

Public ISBD Titre : Principal component analysis Type de document : livre Auteurs : Jolliffe, I.T. Editeur : New York : Springer Année de publication : 1986 Collection : Springer series in statistics Importance : 271 p. ISBN/ISSN/EAN : 978-0-387-96269-6 Note générale : Inventaire 2007: Pointé en rayon Langues : Anglais (eng) Mots-clés : Data analysis  Principal components analysis  Statistical methods Note de contenu : Hbk; Voir aussi la 2ème édition de 2002 à la cote 68494/11 Principal component analysis [livre] / Jolliffe, I.T. . - New York : Springer, 1986 . - 271 p.. - (Springer series in statistics) . ISBN : 978-0-387-96269-6 Inventaire 2007: Pointé en rayon Langues : Anglais (eng) Mots-clés : Data analysis  Principal components analysis  Statistical methods Note de contenu : Hbk; Voir aussi la 2ème édition de 2002 à la cote 68494/11

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
67985	Jol_11_67985	Livre	Salle des ouvrages	11_Mathématiques	Disponible

Simultaneous statistical inference / Miller, R.G. (1981)

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