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Time Series Analysis : Univariate and Multivariate Methods by William W. S. Wei (2005, Hardcover)
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About this product
Product Identifiers
PublisherAddison Wesley
ISBN-100321322169
ISBN-139780321322166
eBay Product ID (ePID)43455636
Product Key Features
Number of Pages640 Pages
Publication NameTime Series Analysis : Univariate and Multivariate Methods
LanguageEnglish
SubjectProbability & Statistics / General, Probability & Statistics / Time Series
Publication Year2005
FeaturesRevised
TypeTextbook
AuthorWilliam W. S. Wei
Subject AreaMathematics
FormatHardcover
Dimensions
Item Height1.2 in
Item Weight37 Oz
Item Length9.3 in
Item Width7.1 in
Additional Product Features
Edition Number2
Intended AudienceCollege Audience
LCCN2004-058701
Dewey Edition22
IllustratedYes
Dewey Decimal519.5/5
Edition DescriptionRevised edition
SynopsisWith its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field., With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Overview. Fundamental Concepts. Stationary Time Series Models. Nonstationary Time Series Models. Forecasting. Model Identification. Parameter Estimation, Diagnostic Checking, and Model Selection. Seasonal Time Series Models. Testing for a Unit Root. Intervention Analysis and Outlier Detection. Fourier Analysis. Spectral Theory of Stationary Processes. Estimation of the Spectrum. Transfer Function Models. Time Series Regression and GARCH Models. Vector Time Series Models. More on Vector Time Series. State Space Models and the Kalman Filter. Long Memory and Nonlinear Processes. Aggregation and Systematic Sampling in Time Series. For all readers interested in time series analysis.
LC Classification NumberQA280.W45 2006
