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Bayesian time series models   Publication : Cambridge, UK | New York Cambridge University Press 2011 . xiii, 417 pages , "'What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they have to say. This ambitious book is the first unified treatment of the emerging knowledge-base in Bayesian time series techniques. Exploiting the unifying framework of probabilistic graphical models, the book covers approximation schemes, both Monte Carlo and deterministic, and introduces switching, multi-object, non-parametric and agent-based models in a variety of application environments. It demonstrates that the basic framework supports the rapid creation of models tailored to specific applications and gives insight into the computational complexity of their implementation. The authors span traditional disciplines such as statistics and engineering and the more recently established areas of machine learning and pattern recognition. Readers with a basic understanding of applied probability, but no experience with time series analysis, are guided from fundamental concepts to the state-of-the-art in research and practice"-- | "Time series appear in a variety of disciplines, from finance to physics, computer science to biology. The origins of the subject and diverse applications in the engineering and physics literature at times obscure the commonalities in the underlying models and techniques. A central aim of this book is an attempt to make modern time series techniques accessible to a broad range of researchers, based on the unifying concept of probabilistic models. These techniques facilitate access to the modern time series literature, including financial time series prediction, video-tracking, music analysis, control and genetic sequence analysis. A particular feature of the book is that it brings together leading researchers that span the more traditional disciplines of statistics, control theory, engineering and signal processing,to the more recent area machine learning and pattern recognition"-- 26 cm. Date : 2011 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1),

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Estimation in conditionally herteroscedastic time series models par Straumann,, Daniel. Publication : [S.l.] Springer 2004 . 250 p. , In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies. 24 cm. Date : 2004 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1),

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Forecasting, time series, and regression par Bowerman, Bruce L. Publication : [S.l.] Cengage Learning 2004 . 720 p. , Awarded Outstanding Academic Book by CHOICE magazine in its first edition, FORECASTING, TIME SERIES, AND REGRESSION: AN APPLIED APPROACH now appears in a fourth edition that illustrates the vital importance of forecasting and the various statistical techniques that can be used to produce them. With an emphasis on applications, this book provides both the conceptual development and practical motivation students need to effectively implement forecasts of their own. Bruce Bowerman, Richard O'Connell, and Anne Koehler clearly demonstrate the necessity of using forecasts to make intelligent decisions in marketing, finance, personnel management, production scheduling, process control, and strategic management. In addition, new technology coverage makes the latest edition the most applied text available on the market. 24 cm. Date : 2004 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1),

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Neural networks and sea time series:reconstruction and extreme-event analysis par Tirozzi, Brunello. Publication : Boston Birkhäuser 2006 . X-179 p. , Devoted to the application of neural networks to the concrete problem of time series of sea data Good reference for a diverse audience of grad students, researchers, and practitioners in applied mathematics, data analysis, meteorlogy, hydraulic, civil and marine engineering Methods, models and alogrithms developed in the work are useful for the construction of sea structures, ports, and marine experiments. 25 cm. Date : 2006 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1),

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Nonlinear time series analysis / par Kantz,, Holger, Publication : Cambridge, UK ; | New York : Cambridge University Press, 2004 . xvi, 369 p. : 26 cm. Date : 2004 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1),

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Permutation complexity in dynamical systems ordinal patterns, permutation entropy and all that par Amigó, José María Publication : Heidelberg Springer 2010 . xv, 249 pages 24 cm. Date : 2010 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (2),

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Time-frequency and time-scale methods : adaptive decompositions, uncertainty principles, and sampling par Hogan, Jeffrey A. Publication : Boston Birkhauser 2005 . xx, 388 pages 25 cm. Date : 2005 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1),

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A handbook of time-series analysis, signal processing and dynamics / par Pollock, D. S. G. Publication : . 1 online resource (xx, 733 pages) : Disponibilité :  http://www.sciencedirect.com/science/book/9780125609906,

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Deconvolution of geophysical time series in the exploration for oil and natural gas / par Silvia, Manuel T. Publication : . 1 online resource (xii, 251 pages) : Disponibilité :  http://www.sciencedirect.com/science/book/9780444416797,

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Time series modelling of water resources and environmental systems / par Hipel, Keith W. Publication : . 1 online resource (xxxvii, 1013 pages) : Disponibilité :  http://www.sciencedirect.com/science/book/9780444892706,

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The spectral analysis of time series / par Koopmans, Lambert H. Publication : . 1 online resource (xvi, 366 pages) : Disponibilité :  http://www.sciencedirect.com/science/book/9780124192515,

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Dynamic stochastic models from empirical data / par Kashyap, Rangasami L. Publication : . 1 online resource (xvi, 334 pages) : Disponibilité :  http://www.sciencedirect.com/science/book/9780124005501,  http://www.sciencedirect.com/science/publication?issn=00765392&volume=122,

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