A Bayesian prediction using the skew Gaussian distribution

Journal of Statistical Planning and Inference

Volumn 120, Issue 1-2, 2004, Pages 85-101

  Kim, Hyoung Moon ^a   Mallick, Bani K ^b  

^a TEXAS A AND M UNIVERSITY CORPUS CHRISTI   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Cross validation; Kriging; Markov chain Monte Carlo; Non Gaussian characteristics

Indexed keywords

EID: 0344154651     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-3758(02)00501-3     Document Type: Article

References (23)

1. Abramowitz M. Stegun I.A. Handbook of Mathematical Functions 1972 Dover New York
2. Azzalini A. Capitanio A. Statistical applications of the multivariate skew normal distribution J. Roy. Statist. Soc. Ser. B 61 1999 579-602
3. Azzalini A. Dalla Valle A. The multivariate skew-normal distribution Biometrika 83 1996 715-726
4. Berger J.O. De Oliveira V. Sansó B. Objective Bayesian analysis of spatially correlated data J. Amer. Statist. Assoc. 96 2001 1361-1374
5. Cressie N.A.C. Statistics for Spatial Data Revised Edition 1993 Wiley New York
6. De Oliveira V. Kedem B. Short D.S. Bayesian prediction of transformed Gaussian random fields J. Amer. Statist. Assoc. 92 1997 1422-1433
7. Fernandez C. Steel M.F.J. On Bayesian modeling of fat tails and skewness J. Amer. Statist. Assoc. 93 1998 359-371
8. Gelfand, A.E., 1996. Model determination using sampling-based methods. In: Gilks, W.R., Richardson, S., Spiegelhalter, D.J. (Eds.), Markov Chain Monte Carlo in Practice. Chapman & Hall, London, pp. 145-161.
9. Gelfand A.E. Smith A.F.M. Sampling-based approaches to calculating marginal densities J. Amer. Statist. Assoc. 85 1990 289-309
10. Gelfand A.E. Dey D.K. Chang H. Model determination using predictive distributions with implementation via sampling-based methods Bayesian Statist. 4 1992 147-167
11. Gelman A. Pasarica C. Dodhia R. Let's practice what we preach: turning tables into graphs Amer. Statist. 56 2002 121-130
12. Gilks W.R. Richardson S. Spiegelhalter D. Markov Chain Monte Carlo in Practice 1996 Chapman & Hall London
13. Graybill F.A. Matrices with Applications in Statistics 1983 Wadsworth Belmont
14. Handcock M.S. Stein M.L. A Bayesian analysis of kriging Technometrics 35 1993 403-410
15. Handcock M.S. Wallis J.R. An approach to statistical spatio-temporal modeling of meteorological fields (with discussion) J. Amer. Statist. Assoc. 89 1994 368-378
16. Meng X.-L. Wong W.H. Simulating ratios of normalizing constants via a simple identity: a theoretical exploration Statist. Sinica 6 1996 831-860
17. Miller D.M. Reducing transformation bias in curve Fitting Amer. Statist. 38 1984 124-126
18. Ripley B.D. Spatial Statistics 1981 Wiley New York
19. Robert C.P. Simulation of truncated normal variables Statist. Comput. 5 1995 121-125
20. Tanner M.A. Tools for Statistical Inference 1996 Springer New York
21. Yaglom A.M. Correlation Theory of Stationary and Related Random Functions I. Basic Results 1987 Springer New York
22. Zellner A. Bayesian and non-Bayesian analysis of the regression model with multivariate student-t error terms J. Amer. Statist. Assoc. 71 1976 400-405
23. Zimmerman D.L. Zimmerman M.B. A comparison of spatial semivariogram estimators and corresponding ordinary kriging predictors Technometrics 33 1991 77-91