A Bayesian analysis of unobserved component models using ox

Journal of Statistical Software

Volumn 41, Issue 13, 2011, Pages 1-24

  Bos, Charles S ^a  

^a VU UNIVERSITY AMSTERDAM   (Netherlands)

Author keywords

Bayes; State space methods; Stochastic volatility; Unobserved components

Indexed keywords

EID: 79961231514     PISSN: None     EISSN: 15487660     Source Type: Journal    
DOI: 10.18637/jss.v041.i13     Document Type: Article

References (21)

1. Bauwens L, Lubrano M, Richard JF (1999). Bayesian Inference in Dynamic Econometric Models. Advanced Texts in Econometrics. Oxford University Press, Oxford.
2. Bos CS (2002). ''A Comparison of Marginal Likelihood Computation Methods. In W Häardle, B Rönz (eds.), COMPSTAT 2002 - Proceedings in Computational Statistics, pp. 111-117. Physica-Verlag, Heidelberg.
3. Bos CS (2003). GnuDraw. URL http://www.tinbergen.nl/~cbos/gnudraw.html.
4. Bos CS, Shephard N (2006). ''Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form. Econometric Reviews, 25(2-3), 219-244.
5. Cappe ́ O, Godsill SJ, Moulines E (2007). ''An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo. Proceedings of the IEEE, 95(5), 899-924.
6. Chib S, Greenberg E (1995). ''Understanding the Metropolis-Hastings Algorithm. The American Statistician, 49(4), 327-335.
7. Commandeur JJF, Koopman SJ, Ooms M (2011). ''Statistical Software for State Space Methods. Journal of Statistical Software, 41(1), 1-18. URL http://www.jstatsoft.org/v41/i01/.
8. Doornik JA (2009). Ox 6: An Object-Oriented Matrix Programming Language. Timberlake Consultants Ltd, London.
9. Durbin J, Koopman SJ (2001). Time Series Analysis by State Space Methods. Oxford University Press, Oxford.
10. Durbin J, Koopman SJ (2002). ''A Simple and Efficient Simulation Smoother for State Space Time Series Analysis. Biometrika, 89(3), 603-615.
11. Geweke J (1992). ''Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments. In JM Bernardo, JO Berger, AP Dawid, AFM Smith (eds.), Bayesian Statistics 4: Proceedings of the Fourth Valencia International Meeting, pp. 169-193. Oxford: Clarendon Press.
12. Harvey AC (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press, Cambridge.
13. Jeffreys H (1961). Theory of Probability. 3rd edition. Oxford University Press, Oxford.
14. Kass RE, Raftery AE (1995).''Bayes Factors. Journal of the American Statistical Association, 90(430), 773-795.
15. Kass RE, Tierney L, Kadane JB (1990). ''The Validity of Posterior Expansions Based on Laplace's Method. In S Geisser (ed.), Bayesian and Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard, pp. 473-488. North Holland, Amsterdam.
16. Kim S, Shephard N, Chib S (1998). ''Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models. Review of Economic Studies, 65(3), 361-393.
17. Koopman SJ, Shephard N, Doornik JA (1999). ''Statistical Algorithms for Models in State Space Using SsfPack 2.2. Econometrics Journal, 2(1), 107-160.
18. Koopman SJ, Shephard N, Doornik JA (2008). SsfPack 3.0: Statistical Algorithms for Models in State Space Form. Timberlake Consultants Ltd, London.
19. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953). ''Equations of State Calculations by Fast Computing Machines. Journal of Chemical Physics, 21, 1087-1091.
20. Pitt MK, Shephard N (1999). ''Filtering via Simulation: Auxiliary Particle Filters. Journal of the American Statistical Association, 94(446), 590-599.
21. Smith AFM, Gelfand AE (1992). ''Bayesian Statistics without Tears: A Sampling-Resampling Perspective. The American Statistician, 46(2), 84-88.