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Zusatztext ...can be recommended to all those researchers engaged in this field! either on a more theoretical basis or with more emphasis on practical issues. Informationen zum Autor Andrew Harvey is Professor of Econometrics at the University of Cambridge. Tommaso Proietti is Professor of Economic Statistics at the University of Udine, Italy Klappentext This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature. Inhaltsverzeichnis Signal Extraction and Likelihood Inference for Linear UC Models 1: Introduction 2: P. Burridge and K.F. Wallis: Prediction Theory for Autoregressive-Moving Average Processes 3: S.J. Koopman: Exact Initial Kalman Filtering and Smoothing for Non-stationary Time Series Models 4: P. de Jong: Smoothing and Interpolation with the State Space Model 5: A.C. Harvey and S.J. Koopman: Diagnostic Checking of Unobserved Components in Time Series Models 6: R. Kohn, C.F. Ansley and C. Wong: Nonparametric Spline Regression with Autoregressive Moving Average Errors Unobserved Components in Economic Time Series 7: Introduction 8: M.W. Watson: Univariate Detrending Methods with Stochastic Trends 9: A.C. Harvey and A. Jaeger: Detrending, Stylized Facts and the Business Cycle 10: A. Maravall: Stochastic Linear Trends, Models and Estimators 11: D. Pfeffermann: Estimation and Seasonal Adjustment of Population Means Using Data from Repeated Surveys 12: A.C. Harvey, S.J. Koopman and M. Riani: The Modelling and Seasonal Adjustment of Weekly Observations Testing in Unobserved Components Models 13: Introduction 14: J. Nyblom: Testing for Deterministic Linear Trends in a Times Series 15: F. Canova and B.E. Hansen: Are Seasonal Patterns Stable Over Time? A Test for Seasonal Stability Non-Linear and Non- Gaussian Models 16: Introduction 17: A.C. Harvey and C. Fernandes: Times Series Models for Count Data or Qualitative Observations 18: Carter and Kohn: On Gibbs Sampling for State Space Models 19: P. de Jong and N. Shephard: The Simulation Smoother 20: N. Shephard and M.K. Pitt: Likelihood Analysis of Non-Gaussian Measurement Time Series 21: J. Durbin and S.J. Koopman: Time Series Analysis of Non-Gaussian Observations based on State Space Models from both Classical and Bayesian Perspectives 22: S. Kim, N. Shephard, and S. Chib: Stochastic Volatility: Liklihood Inference and Comparison with ARCH Models 23: A. Doucet, S.J. Godsill, and C. Andrieu: On Sequential Monte Carlo Sampling Methods for Bayesian Filtering ...
