Diagnostic Checks in Time Series

AvWai Keung Li

Inbunden, Engelska, 2003

Del i serien Chapman & Hall/CRC Monographs on Statistics and Applied Probability

2 682 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

E-bok

2 998 kr

Beskrivning

Diagnostic checking is an important step in the modeling process. But while the literature on diagnostic checks is quite extensive and many texts on time series modeling are available, it still remains difficult to find a book that adequately covers methods for performing diagnostic checks.Diagnostic Checks in Time Series helps to fill that gap. Author Wai Keung Li--one of the world's top authorities in time series modeling--concentrates on diagnostic checks for stationary time series and covers a range of different linear and nonlinear models, from various ARMA, threshold type, and bilinear models to conditional non-Gaussian and autoregressive heteroscedasticity (ARCH) models. Because of its broad applicability, the portmanteau goodness-of-fit test receives particular attention, as does the score test. Unlike most treatments, the author's approach is a practical one, and he looks at each topic through the eyes of a model builder rather than a mathematical statistician.This book brings together the widely scattered literature on the subject, and with clear explanations and focus on applications, it guides readers through the final stages of their modeling efforts. With Diagnostic Checks in Time Series, you will understand the relative merits of the models discussed, know how to estimate these models, and often find ways to improve a model.

Produktinformation

Utgivningsdatum:2003-12-29
Mått:152 x 229 x 20 mm
Vikt:550 g
Format:Inbunden
Språk:Engelska
Serie:Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Antal sidor:210
Förlag:Taylor & Francis Inc
ISBN:9781584883371

Utforska kategorier

Mer om författaren

Li, Wai Keung

Recensioner i media

"There are many books on time series analysis but this is the first monograph specialized to diagnostic checking. … The author is a known specialist in time series modelling. His approach is a practical one and each topic is presented from a model builder's point of view. … [V]ery useful for statisticians working in time series analysis."- EMS Newsletter"[T]he author has adopted an easy-to-follow style which takes the reader to the frontier of the literature painlessly."- Journal of the Royal Statistical Society"There have been several excellent monographs on the diagnostics of linear models, but this is the first and possibly definitive one for stationary time series modeling. It is of great value in bringing together the diverse literature on the topic, over three hundred references are given, and integrating them into a coherent whole…Whatever type of time series model you are fitting, linear or nonlinear, volatile or not, turn to this monograph for help in testing its goodness-of-fit."- ISI Short Book Reviews

Innehållsförteckning

INTRODUCTIONDIAGNOSTIC CHECKS FOR UNIVARIATE LINEAR MODELSIntroductionThe Asymptotic Distribution of the Residual Autocorrelation DistributionModifications of the Portmanteau StatisticExtension to Multiplicative Seasonal ARMA ModelsRelation with the Lagrange Multiplier TestA Test Based on the Residual Partial Autocorrelation testA Test Based on the Residual Correlation Matrix testExtension to Periodic AutoregressionsTHE MULTIVARIATE LINEAR CASEThe Vector ARMA modelGranger Causality TestsTransfer Function Noise (TFN) ModelingROBUST MODELING AND ROBUST DIAGNOSTIC CHECKINGA Robust Portmanteau TestA Robust Residual Cross-Correlation TestA Robust Estimation Method for Vector Time SeriesThe Trimmed Portmanteau StatisticNONLINEAR MODELSIntroductionTests for General Nonlinear StructureTests for Linear vs. Specific Nonlinear ModelsGoodness-of-Fit Tests for Nonlinear Time SeriesChoosing Two Different Families of Nonlinear ModelsCONDITIONAL HETEROSCEDASTICITY MODELSThe Autoregressive Conditional Heteroscedastic ModelChecks for the Presence of ARCHDiagnostic Checking for ARCH ModelsDiagnostics for Multivariate ARCH modelsTesting for Causality in the VarianceFRACTIONALLY DIFFERENCED PROCESSIntroductionMethods of EstimationA Model Diagnostic StatisticDiagnostics for Fractional DifferencingMISCELLANEOUS MODELS AND TOPICSARMA Models with Non-Gaussian ErrorsOther Non-Gaussian time SeriesThe Autoregressive Conditional Duration ModelA Power Transformation to Induce NormalityEpilogue