Generalized spatial dynamic factor models

Computational Statistics and Data Analysis

Volumn 55, Issue 3, 2011, Pages 1319-1330

  Lopes, Hedibert Freitas ^a   Gamerman, Dani ^b   Salazar, Esther ^c  

^a UNIVERSITY OF CHICAGO   (United States)

^b FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^c DUKE UNIVERSITY   (United States)

Author keywords

Exponential family; Factor model; Gaussian process; Markov chain Monte Carlo; Reversible jump; Sampling schemes

Indexed keywords

EXPONENTIAL FAMILY; FACTOR MODEL; GAUSSIAN PROCESSES; MARKOV CHAIN MONTE CARLO; REVERSIBLE JUMP; SAMPLING SCHEMES;

GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); MARKOV PROCESSES; MONTE CARLO METHODS; SPEECH RECOGNITION; UNCERTAINTY ANALYSIS;

UNCERTAIN SYSTEMS;

EID: 78649330399     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2010.09.020     Document Type: Article

References (23)

1. C.K. Carter, and R. Kohn On Gibbs sampling for state space models Biometrika 81 1994 541 553
2. N. Cressie, and H. Huang Classes of nonseparable, spatio-temporal stationary covariance functions Journal of the American Statistical Association 94 1999 1330 1340
3. J.A. Doornik Object-Oriented Matrix Programming using Ox 3rd ed 2002 Timberlake Consultants Press and Oxford London
4. M.V. Fernandes, A.M. Schmidt, and H.S. Migon Modelling zero-inflated spatio-temporal processes Statistical Modelling 9 1 2009 3 25
5. S. Frhwirth-Schnatter Data augmentation and dynamic linear models Journal of Time Series Analysis 15 1994 183 202
6. K.R. Gabriel, and J. Neumann A Markov chain model for daily rainfall occurrences at Tel Aviv Quarterly Journal Royal Meteorological Society 88 1962 90 95
7. D. Gamerman Markov chain Monte Carlo for dynamic generalised linear models Biometrika 85 1998 215 227
8. D. Gamerman, and H.F. Lopes Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference 2nd ed 2006 Chapman and Hall/CRC Boca Raton, USA
9. A. Gelman, and D. Rubin Inference from iterative simulation using multiple sequences Statistical Science 7 1992 457 511
10. J. Hoeting, D. Madigan, A. Raftery, and C. Volinsky Bayesian model averaging (with discussion) Statistical Science 14 1999 382 401
11. M. Hooten, and C. Wikle A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove Environmental and Ecological Statistics 15 2008 59 70
12. J.P. Hughes, P. Guttorp, and S.P. Charles A non-homogeneous hidden Markov model for precipitation occurrence Journal of the Royal Statistical Society: Series C (Applied Statistics) 48 1999 15 30
13. X. Jin, B. Carlin, and S. Banerjee Generalized hierarchical multivariate CAR models for areal data Biometrics 61 2005 950 961
14. G. Kitagawa Non-Gaussian state-space modeling of non-stationary time series Journal of the American Statistical Association 82 1987 1032 1041
15. L. Knorr-Held Conditional prior proposals in dynamic models Scandinavian Journal of Statistics 26 1999 129 144
16. L. Knorr-Held, and N.G. Best A shared component model for detecting joint and selective clustering of two diseases Journal of the Royal Statistical Society, Series A 164 2001 73 85 (Pubitemid 33392803)
17. H.F. Lopes, and C.M. Carvalho Factor stochastic volatility with time varying loadings and Markov switching regimes Journal of Statistical Planning and Inference 137 2007 3082 3091
18. H.F. Lopes, E. Salazar, and D. Gamerman Spatial dynamic factor models Bayesian Analysis 3 2008 759 792
19. H.F. Lopes, and M. West Bayesian model assessment in factor analysis Statistica Sinica 14 2004 41 67
20. H.S. Migon, D. Gamerman, H.F. Lopes, and M.A.R. Ferreira Dynamic Models D.K. Dey, C. Rao, Handbook of Statistics: Bayesian Thinking, Modeling and Computation vol. 25 2005 Noth Holland
21. R.D. Stern, and R. Coe A model fitting analysis of daily rainfall data Journal of the Royal Statistical Society, Series A 147 1984 1 34
22. F. Wang, and M.M. Wall Generalized common spatial factor model Biostatistics 4 2003 569 582
23. M. West, and P. Harrison Bayesian Forecasting and Dynamic Models 1997 Springer New York