Correction: Function estimation with locally adaptive dynamic models (Computational Statistics, (2002), 17, 479, 10.1007/s001800200121);Function estimation with locally adaptive dynamic models

Computational Statistics

Volumn 17, Issue 4, 2002, Pages 479-499

  Lang, Stefan ^a   Fronk, Eva Maria ^a   Fahrmeir, Ludwig ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

Adaptive smoothing; MCMC; Nonparametric Bayesian regression; Random walk priors; Unsmooth functions; Variable smoothing parameter

Indexed keywords

EID: 0036448882     PISSN: 09434062     EISSN: 16139658     Source Type: Journal    
DOI: 10.1007/BF02753919     Document Type: Erratum

References (28)

1. k-smoothing splines. Journal of Statistical Planning and Inference, 49, 327-341.
2. Aykroyd, R. (1998), Bayesian estimation for homogeneous and inhomogeneous Gaussian random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20, 533-539.
3. Besag, J., Green, P., Higdon, D. and Mengersen, K. (1995), Bayesian computation and stochastic systems, Statist. Sci., 10, 3-66.
4. Biller, C. (2000), Adaptive Bayesian regression splines in semiparametric generalized linear models. J. Comp. and Graph. Stat., 12, 122-140.
5. Carter, C.K. and Kohn, R. (1994), On Gibbs sampling for state space models. Biometrica, 81, 541-553.
6. Carter, C.K. and Kohn, R. (1996a), Markov chain Monte Carlo in conditionally Gaussian state space models. Biometrika 83, 589-601.
7. Carter, C.K. and Kohn, R. (1996b), Robust Bayesian nonparametric regression. In Statistical Theory and Computational Aspects of Smoothing, eds. Hrdle, W. and Schimek, M.G., Physica-Verlag, Heidelberg, 1996.
8. Denison, D.G.T., Mallick, B.K. and Smith, A.F.M. (1998), Automatic Bayesian curve fitting. J.R. Statist. Soc. B, 60, 333-350.
9. Donoho, D.L. and Johnstone, I.M. (1994), Ideal spatial adaption by wavelet shrinkage. Biometrika, 81, 425-455.
10. Fahrmeir, L. and Künstler, R. (1999), Penalized likelihood smoothing in robust state space models. Metrika 49, 173-191.
11. Fahrmeir, L. and Lang, S. (2001), Bayesian inference for generalized additive mixed models based on Markov random field priors. Appl. Statist. (JRSS C), 50, 201-220.
12. Fahrmeir, L. and Tutz, G. (2001), Multivariate statistical modelling based on generalized linear models. Springer-Verlag, New York.
13. Fan, J. and Gijbels, I. (1995), Data-driven bandwidth selection in local polynomial filting: variable bandwidth and spatial adaption. J.R. Statist. Soc. B 57, 371-394.
14. Fruehwirth-Schnatter, S. (1994), Data augmention and dynamic linear models. Journal of Time Series Analysis, 15, 183-202.
15. Harvey, A.C. (1989), Forecasting, structural time series models and the Kalman filter, Cambridge University Press, Cambridge.
16. Knorr-Held, L. (1999), Conditional prior proposals in dynamic models. Scand. J. Statist., 26, 129-144.
17. Kohn, R. and Ansley, C.F. (1987), A new algorithm for spline smoothing based on smoothing a stochastic process. SIAM J. of Sci. and Statist. Comp., 8, 33-48.
18. Lang, S. and Brezger, A. (2001), Bayesian P-splines. SFB 386 Discussion Paper 336, University of Munich.
19. Rue, H. (2001), Fast sampling of Gaussian Markov random fields. J.R. Statist. Soc., 63, 325-338.
20. Ruppert, D. and Carroll, R.J. (2000), Spatially adaptive penalties for spline fitting. Australian and New Zealand Journal of Statistics, 42, 205-223.
21. Seifert, B. and Gasser T. (2000), Data adaptive ridging in local polynomial regression. J. Comp. and Graph. Stat. 9, 338-360.
22. Shephard, N., and Pitt, P. (1997), Likelihood analysis on non-Gaussian measurement time series. Biometrika 84, 653-667.
23. Smith, M. and Kohn, R. (1996), Nonparametric regression using Bayesian variable selection. Journal of Econometrics, 75, 317-343.
24. Smith, M. and Kohn, R., (1997), A Bayesian approach to nonparametric bivariate regression. J. Am. Statist. Ass., 92, 1522-1535.
25. Spiegelhalter, D.J., Best, N.G., Carlin, B.P. and van der Linde (2001), Bayesian deviance, the effective number of parameters, and the comparison of arbitrary complex models. Preprint.
26. Stone, C.J., Hansen, M. and Kooperberg, C. and Troung (1997), Polynomial splines and their tensor products in extended linear modeling (with discussion) Ann. Statist., 25, 1371-1470.
27. Taylor, St. J. (1986), Modelling financial time series. John Wiley, Chichester.
28. Whittaker, E.T. (1923), On a new method of graduation. Proceedings of Edinburgh Mathmatical Society, 41, 63-75.