On Estimation and Prediction for Spatial Generalized Linear Mixed Models

Citations

Cited by:

1. Varin, Cristiano & Host, Gudmund & Skare, Oivind, 2005. "Pairwise likelihood inference in spatial generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1173-1191, June.
2. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
3. Robert Richardson, 2022. "Spatial Generalized Linear Models with Non-Gaussian Translation Processes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 4-21, March.
4. Jo Eidsvik & Sara Martino & Håvard Rue, 2009. "Approximate Bayesian Inference in Spatial Generalized Linear Mixed Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(1), pages 1-22, March.
5. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
   • Baltagi, Badi H., 2006. "Forecasting with panel data," Discussion Paper Series 1: Economic Studies 2006,25, Deutsche Bundesbank.
   • Badi H. Baltagi, 2007. "Forecasting with Panel Data," Center for Policy Research Working Papers 91, Center for Policy Research, Maxwell School, Syracuse University.
6. Farman Ali & Zulfiqar Ali & Bing-Zhao Li & Sadia Qamar & Amna Nazeer & Saba Riaz & Muhammad Asif Khan & Rabia Fayyaz & Javeria Nawaz Abbasi, 2022. "Exploring Regional Profile of Drought History- a New Procedure to Characterize and Evaluate Multi-Scaler Drought Indices Under Spatial Poisson Log-Normal Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 2989-3005, July.
7. Marco Minozzo & Luca Bagnato, 2021. "A unified skew‐normal geostatistical factor model," Environmetrics, John Wiley & Sons, Ltd., vol. 32(4), June.
8. Jaewoo Park & Sangwan Lee, 2022. "A projection‐based Laplace approximation for spatial latent variable models," Environmetrics, John Wiley & Sons, Ltd., vol. 33(1), February.
9. Tatiyana V. Apanasovich & David Ruppert & Joanne R. Lupton & Natasa Popovic & Nancy D. Turner & Robert S. Chapkin & Raymond J. Carroll, 2008. "Aberrant Crypt Foci and Semiparametric Modeling of Correlated Binary Data," Biometrics, The International Biometric Society, vol. 64(2), pages 490-500, June.
10. Mahmoud, Hamdy F.F. & Kim, Inyoung, 2019. "Semiparametric spatial mixed effects single index models," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 108-122.
11. J. Zhu & J. C. Eickhoff & P. Yan, 2005. "Generalized Linear Latent Variable Models for Repeated Measures of Spatially Correlated Multivariate Data," Biometrics, The International Biometric Society, vol. 61(3), pages 674-683, September.
12. Marco Minozzo & Clarissa Ferrari, 2013. "Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy): spatial special issue," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(2), pages 195-213, April.
13. Zhang, Tonglin, 2019. "General Gaussian estimation," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 234-247.
14. F. Nathoo & C. B. Dean, 2007. "A Mixed Mover–Stayer Model for Spatiotemporal Two-State Processes," Biometrics, The International Biometric Society, vol. 63(3), pages 881-891, September.
15. Wolfgang Jank & P. K. Kannan, 2005. "Understanding Geographical Markets of Online Firms Using Spatial Models of Customer Choice," Marketing Science, INFORMS, vol. 24(4), pages 623-634, December.
16. De Oliveira, Victor, 2013. "Hierarchical Poisson models for spatial count data," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 393-408.
17. Hosseini, Fatemeh & Eidsvik, Jo & Mohammadzadeh, Mohsen, 2011. "Approximate Bayesian inference in spatial GLMM with skew normal latent variables," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1791-1806, April.
18. Cristiano Varin, 2008. "On composite marginal likelihoods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 1-28, February.
19. Victor De Oliveira, 2017. "Geostatistical Binary Data: Models, Properties And Connections," Working Papers 0151mss, College of Business, University of Texas at San Antonio.
20. Soubeyrand, Samuel & Chadoeuf, Joel, 2007. "Residual-based specification of a hidden random field included in a hierarchical spatial model," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6404-6422, August.
21. Xiaotian Zheng & Athanasios Kottas & Bruno Sansó, 2023. "Bayesian geostatistical modeling for discrete‐valued processes," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.
22. Marco Minozzo & Clarissa Ferrari, 2011. "Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy)," Working Papers 21/2011, University of Verona, Department of Economics.
23. Baghishani, Hossein & Mohammadzadeh, Mohsen, 2011. "A data cloning algorithm for computing maximum likelihood estimates in spatial generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1748-1759, April.
24. Oscar O. Melo & Carlos E. Melo & Jorge Mateu, 2016. "Beta spatial linear mixed model with variable dispersion using Monte Carlo maximum likelihood," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(1), pages 47-76, February.
25. Jing, Liang & De Oliveira, Victor, 2015. "geoCount: An R Package for the Analysis of Geostatistical Count Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i11).
26. Soubeyrand, Samuel & Enjalbert, Jérôme & Sache, Ivan, 2008. "Accounting for roughness of circular processes: Using Gaussian random processes to model the anisotropic spread of airborne plant disease," Theoretical Population Biology, Elsevier, vol. 73(1), pages 92-103.