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Signal Extraction and Likelihood Inference for Linear UC Models
1. Introduction
2. Prediction Theory for Autoregressive-Moving Average Processes, P. Burridge and K.F. Wallis
3. Exact Initial Kalman Filtering and Smoothing for Non-stationary Time Series Models, S.J. Koopman
4. Smoothing and Interpolation with the State Space Model, P. de Jong
5. Diagnostic Checking of Unobserved Components in Time Series Models, A.C. Harvey and S.J. Koopman
6. Nonparametric Spline Regression with Autoregressive Moving Average Errors, R. Kohn, C.F. Ansley and C. Wong
Unobserved Components in Economic Time Series
7. Introduction
8. Univariate Detrending Methods with Stochastic Trends, M.W. Watson
9. Detrending, Stylized Facts and the Business Cycle, A.C. Harvey and A. Jaeger
10. Stochastic Linear Trends, Models and Estimators, A. Maravall
11. Estimation and Seasonal Adjustment of Population Means Using Data from Repeated Surveys, D. Pfeffermann
12. The Modelling and Seasonal Adjustment of Weekly Observations, A.C. Harvey, S.J. Koopman and M. Riani
Testing in Unobserved Components Models
13. Introduction
14. Testing for Deterministic Linear Trends in a Times Series, J. Nyblom
15. Are Seasonal Patterns Stable Over Time? A Test for Seasonal Stability, F. Canova and B.E. Hansen
Non-Linear and Non- Gaussian Models
16. Introduction
17. Times Series Models for Count Data or Qualitative Observations, A.C. Harvey and C. Fernandes
18. On Gibbs Sampling for State Space Models, Carter and Kohn
19. The Simulation Smoother, P. de Jong and N. Shephard
20. Likelihood Analysis of Non-Gaussian Measurement Time Series, N. Shephard and M.K. Pitt
21. Time Series Analysis of Non-Gaussian Observations based on State Space Models from both Classical and Bayesian Perspectives, J. Durbin and S.J. Koopman
22. Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models, S. Kim, N. Shephard, and S. Chib
23. On Sequential Monte Carlo Sampling Methods for Bayesian Filtering, A. Doucet, S.J. Godsill, and C. Andrieu
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Add Readings in Unobserved Components Models: Advanced Texts in Econometrics, 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 , Readings in Unobserved Components Models: Advanced Texts in Econometrics to the inventory that you are selling on WonderClubX
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Add Readings in Unobserved Components Models: Advanced Texts in Econometrics, 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 , Readings in Unobserved Components Models: Advanced Texts in Econometrics to your collection on WonderClub |