Time Series Analysis and Its Applications

With R Examples

Robert H. Shumway, David s. Stoffer - Collection Springer texts in statistics

600 pages, parution le 18/07/2006 (2^eme édition)

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Résumé

Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using non-trivial data illustrate solutions to problems such as evaluating pain perception experiments using magnetic resonance imaging or monitoring a nuclear test ban treaty. The book is designed to be useful as a text for graduate level students in the physical, biological and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course.

Theory and methodology are separated to allow presentations on different levels. Material from the earlier 1988 Prentice-Hall text Applied Statistical Time Series Analysis has been updated by adding modern developments involving categorical time sries analysis and the spectral envelope, multivariate spectral methods, long memory series, nonlinear models, longitudinal data analysis, resampling techniques, ARCH models, stochastic volatility, wavelets and Monte Carlo Markov chain integration methods. These add to a classical coverage of time series regression, univariate and multivariate ARIMA models, spectral analysis and state-space models. The book is complemented by ofering accessibility, via the World Wide Web, to the data and an exploratory time series analysis program ASTSA for Windows that can be downloaded as Freeware.

Written for: Graduate students

L'auteur - Robert H. Shumway

Robert H. Shumway is Professor of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the Inernational Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is the author of a previous 1988 Prentice-Hall text on applied time series analysis and is currenlty a Departmental Editor for the Journal of Forecasting.

L'auteur - David s. Stoffer

David S. Stoffer is Professor of Statistics at the University of Pittsburgh. He has made seminal contributions to the analysis of categorical time series and won the 1989 American Statistical Association Award for Outstanding Statistical Application in a joint paper analyzing categorical time series arising in infant sleep-state cycling. He is currently an Associate Editor of the Journal of Forecasting and has served as an Associate Editor for the Journal fo the American Statistical Association.

Sommaire

Characteristics of time series
Time series regression and exploratory data analysis
ARIMA models
Spectral analysis and filtering
Additional time domain topics
State-space models
Statistical methods in the frequency domain

A Large sample theory
B Time domain theory
C Spectral domain theory

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Robert H. Shumway, David s. Stoffer
Collection	Springer texts in statistics
Parution	18/07/2006
Édition	2^eme édition
Nb. de pages	600
Format	16 x 24
Couverture	Relié
Poids	980g
Intérieur	Noir et Blanc
EAN13	9780387293172
ISBN13	978-0-387-29317-2