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Nonlinear Time Series

Theory, Methods and Applications with R Examples

Language EnglishEnglish
E-book Adobe ePub DRM
Publishers Chapman and Hall/CRC, January 2014
This text emphasizes nonlinear models for a course in time series analysis. After introducing stocha... Full description
? points 426 b
62 113 Ft
In stock Immediate digital delivery

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.

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About the book

Full name Nonlinear Time Series
Author Randal Douc, Eric Moulines, David Stoffer
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2014
Number of pages 551
EAN 9781040064542
Libristo code 45153441
Publishers Chapman and Hall/CRC

Categories

Economics, Finance, Business & Management > Economics > Econometrics & economic statistics
Mathematics & Science > Mathematics > Probability & statistics
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