Nonstationary multivariate process modeling through spatially varying coregionalization
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Volume (Year): 13 (2004)
Issue (Month): 2 (December)
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Web page: http://www.springerlink.com/link.asp?id=120411
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- Montserrat Fuentes, 2002. "Spectral methods for nonstationary spatial processes," Biometrika, Biometrika Trust, vol. 89(1), pages 197-210, March.
- Browne, William J. & Draper, David & Goldstein, Harvey & Rasbash, Jon, 2002. "Bayesian and likelihood methods for fitting multilevel models with complex level-1 variation," Computational Statistics & Data Analysis, Elsevier, vol. 39(2), pages 203-225, April.
- Alexandra M. Schmidt & Ajax R. B. Moreira & Thais C. O. Fonseca & Steven M. Helfand, 2006.
"Spatial Stochastic Frontier Models: accounting for unobserved local determinants of inefficiency,"
1220, Instituto de Pesquisa Econômica Aplicada - IPEA.
- Alexandra Schmidt & Ajax Moreira & Steven Helfand & Thais Fonseca, 2009. "Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 31(2), pages 101-112, April.
- Li, Bo & Zhang, Hao, 2011. "An approach to modeling asymmetric multivariate spatial covariance structures," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1445-1453, November.
- David Wheeler & Catherine Calder, 2007. "An assessment of coefficient accuracy in linear regression models with spatially varying coefficients," Journal of Geographical Systems, Springer, vol. 9(2), pages 145-166, June.
- José-María Montero-Lorenzo & Beatriz Larraz-Iribas & Antonio Páez, 2009. "Estimating commercial property prices: an application of cokriging with housing prices as ancillary information," Journal of Geographical Systems, Springer, vol. 11(4), pages 407-425, December.
- Sain, Stephan R. & Cressie, Noel, 2007. "A spatial model for multivariate lattice data," Journal of Econometrics, Elsevier, vol. 140(1), pages 226-259, September.
- Finley, Andrew O. & Sang, Huiyan & Banerjee, Sudipto & Gelfand, Alan E., 2009. "Improving the performance of predictive process modeling for large datasets," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2873-2884, June.
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