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Nonlinear Times Series: Theory, Methods and Applications With R Examples

Randal Douc (Telecom SudParis, Evry, France), Eric Moulines (Telcom Praris Tech, Paris, France), David S. Stoffer (University of Pittsburgh, Pennsylvania, USA)
Format
Book
Published
Boca Raton : CRC Press, taylor & Francis Group, [2014]
Language
English
Series
Chapman & Hall/CRC Texts in Statistical Science Series
Texts in Statistical Science
ISBN
9781466502253, 1466502258
Related Resources
Cover image
Summary
"This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference"--
Description
xx, 531 pages ; 25 cm.
Notes
Includes bibliographical references (pages 505-525)and index.
Technical Details
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  • Staff View

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    a| Nonlinear times series : b| theory, methods and applications with R examples / c| Randal Douc (Telecom SudParis, Evry, France), Eric Moulines (Telcom Praris Tech, Paris, France), David S. Stoffer (University of Pittsburgh, Pennsylvania, USA).
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    a| Includes bibliographical references (pages 505-525)and index.
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Math Stacks N/A Available