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State Space and Unobserved Component Models -

State Space and Unobserved Component Models

Theory and Applications
Buch | Softcover
398 Seiten
2012
Cambridge University Press (Verlag)
978-1-107-40743-5 (ISBN)
CHF 78,50 inkl. MwSt
This 2004 volume offers a broad overview of developments in the theory and applications of state space modeling. With contributions from renowned experts, it offers a unique synthesis of state space methods and unobserved component models, important in a wide range of subjects, including economics, finance, medicine and engineering.
This 2004 volume offers a broad overview of developments in the theory and applications of state space modeling. With fourteen chapters from twenty-three contributors, it offers a unique synthesis of state space methods and unobserved component models that are important in a wide range of subjects, including economics, finance, environmental science, medicine and engineering. The book is divided into four sections: introductory papers, testing, Bayesian inference and the bootstrap, and applications. It will give those unfamiliar with state space models a flavour of the work being carried out as well as providing experts with valuable state of the art summaries of different topics. Offering a useful reference for all, this accessible volume makes a significant contribution to the literature of this discipline.

Part I. State Space Models: 1. Introduction to state space time series analysis James Durbin; 2. State structure, decision making and related issues Peter Whittle; 3. An introduction to particle filters Simon Maskell; Part II. Testing: 4. Frequence domain and wavelet-based estimation for long-memory signal plus noise models Katsuto Tanaka; 5. A goodness-of-fit test for AR (1) models and power against state-space alternatives T. W. Anderson and Michael A. Stephens; 6. Test for cycles Andrew C. Harvey; Part III. Bayesian Inference and Bootstrap: 7. Efficient Bayesian parameter estimation Sylvia Frühwirth-Schnatter; 8. Empirical Bayesian inference in a nonparametric regression model Gary Koop and Dale Poirier; 9. Resampling in state space models David S. Stoffer and Kent D. Wall; Part IV. Applications: 10. Measuring and forecasting financial variability using realised variance Ole E. Barndorff-Nielsen, Bent Nielsen, Neil Shephard and Carla Ysusi; 11. Practical filtering for stochastic volatility models Jonathan R. Stroud, Nicholas G. Polson and Peter Müller; 12. On RegComponent time series models and their applications William R. Bell; 13. State space modeling in macroeconomics and finance using SsfPack in S+Finmetrics Eric Zivot, Jeffrey Wang and Siem Jan Koopman; 14. Finding genes in the human genome with hidden Markov models Richard Durbin.

Erscheint lt. Verlag 13.9.2012
Verlagsort Cambridge
Sprache englisch
Maße 170 x 241 mm
Gewicht 630 g
Themenwelt Wirtschaft Volkswirtschaftslehre Ökonometrie
ISBN-10 1-107-40743-5 / 1107407435
ISBN-13 978-1-107-40743-5 / 9781107407435
Zustand Neuware
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