Parallel Bayesian MCMC imputation for multiple distributed lag models: A case study in environmental epidemiology

Handbook of Markov Chain Monte Carlo

Volumn , Issue , 2011, Pages 493-512

  Caffo, Brian ^a   Peng, Roger ^a   Dominici, Francesca ^a   Louis, Thomas A ^a   Zeger, Scott ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85026310219     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (31)

1. Barnett, G., Kohn, R., and Sheather, S. 1996. Bayesian estimation of an autoregressive model using Markov chain Monte Carlo. Journal of Econometrics, 74:237-254
2. Beguelin, A., Dongarra, J., Jiang, W., Manchek, R., and Sunderam, V. 1995. PVM: Parallel Virtual Machine: A Users' Guide and Tutorial for Networked Parallel Computing. MIT Press, Cambridge, MA
3. Bell, M., McDermott, A., Zeger, S., Samet, J., and Dominici, F. 2004. Ozone and short-term mortality in 95 urban communities, 1987-2000. Journal of the American Medical Association, 292(19):2372-2378
4. Broersen, P., de Waele, S., and Bos, R. 2004. Autoregressive spectral analysis when observations are missing. Automatica, 40(9):1495-1504
5. Carlin, B. and Louis, T. 2009. Bayesian Methods for Data Analysis, 3rd edn. Chapman & Hall/CRC Press, Boca Raton, FL
6. Diggle, P. 1990. Times Series: A Biostatistical Introduction. Oxford University Press, Oxford
7. Dominici, F., McDermott, A., Zeger, S., and Samet, J. 2002. On the use of generalized additive models in time-series studies of air pollution and health. American Journal of Epidemiology, 156(3):193
8. Dominici, F., Peng, R., Bell, M., Pham, L., McDermott, A., Zeger, S., and Samet, J. 2006. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. Journal of the American Medical Association, 295(10):1127-1134
9. Durbin, J. 1960. The fitting of time series models. International Statistical Review, 28:233-244
10. Fill, J. 1998. An interruptible algorithm for perfect sampling via Markov chains. Annals of Applied Probability, 8(1):131-162
11. Fill, J., Machida, M., Murdoch, D., and Rosenthal, J. 2000. Extension of Fill's perfect rejection sampling algorithm to general chains. Random Structures and Algorithms, 17(3-4):290-316
12. Gelman, A. and Rubin, D. 1992. Inference from iterative simulation using multiple sequences. Statistical Science, 7:457-511
13. Geyer, C. 1992. Practical Markov chain Monte Carlo. Statistical Science, 7:473-511
14. Hobert, J., Jones, G., Presnell, B., and Rosenthal, J. 2002. On the applicability of regenerative simulation in Markov chain Monte Carlo. Biometrika, 89(4):731-743
15. Huerta, G. and West, M. 1999. Priors and component structures in autoregressive time series models. Journal of the Royal Statistical Society, Series B, 61(4):881-899
16. Jones, G., Haran, M., Caffo, B., and Neath, R. 2006. Fixed-width output analysis for Markov chain Monte Carlo. Journal of the American Statistical Association, 101(476):1537-1547
17. Kontoghiorghes, E. 2006. Handbook of Parallel Computing and Statistics. Chapman & Hall/CRC, Boca Raton, FL
18. Little, R. and Rubin, D. 2002. Statistical Analysis with Missing Data, 2nd edn. Wiley, Hoboken, NJ
19. Monahan, J. 1983. Fully Bayesian analysis of ARMAtime series models. Journal of Econometrics, 21:307-331
20. Monahan, J. and Boos, D. 1992. Proper likelihoods for Bayesian analysis. Biometrika, 79(2):271-278
21. Mykland, P., Tierney, L., and Yu, B. 1995. Regeneration in Markov chain samplers. Journal of the American Statistical Association, 90(429):233-241
22. Propp, J. and Wilson, D. 1998. How to get a perfectly random sample from a generic Markov chain and generate a random spanning tree of a directed graph. Journal of Algorithms, 27(2):170-217
23. Rosenthal, J. 2000. Parallel computing and Monte Carlo algorithms. Far East Journal of Theoretical Statistics, 4(2):207-236
24. Rossini, A., Tierney, L., and Li, N. 2007. Simple parallel statistical computing in R. Journal of Computational and Graphical Statistics, 16(2):399
25. Samet, J., Dominici, F., Currieo, F., Coursac, I., and Zeger, S. 2000. Fine particulate air pollution and mortality in 20 U.S. cities 1987-1994. New England Journal of Medicine, 343(24):1742-1749
26. Schwartz, J. 2000. Harvesting and long term exposure effects in the relation between air pollution and mortality. American Journal of Epidemiology, 151(5):440
27. Snir, M., Otto, S., Walker, D., Dongarra, J., and Huss-Lederman, S. 1995. MPI: The Complete Reference. MIT Press, Cambridge, MA
28. Wallin, R. and Isaksson, A. 2002. Multiple optima in identification of ARX models subject to missing data. EURASIP Journal on Applied Signal Processing, 1:30-37
29. Winkler, G. 2003. Image Analysis, Random Fields, and Dynamic Monte Carlo Methods, 2nd edn. Springer, Berlin
30. Zanobetti, A., Wand, M. P., Schwartz, J., and Ryan, L. M. 2000. Generalized additive distributed lag models: Quantifying mortality displacement. Biostatistics, 1(3):279-292
31. Zeger, S., Dominici, F., and Samet, J. 1999. Harvesting-resistant estimates of air pollution effects on mortality. Epidemiology, 10(2):171