POSTERS

• Abellana R. and Ascaso C., Partial likelihood for a spatial-temporal non randomness point process

• Barber, A., Barber, X., Mayoral, A. M., and Morales, J., A case study of Bayesian geostatistics: Bioclimatic classification of the island of Cyprus

• Beamonte, A., Gargallo, P., and Salvador, M., Bayesian selection of spatio-temporal autoregressive models of neighbourhood effects: An application to the Zaragoza real estate market

• Beneš V., On a class of Cox point processes

• Bevilacqua, M., Gaetan, C. , Porcu, E., and Mateu J., Composite likelihood methods for space-time data

• Botella, F., López-Quílez, A., Mayoral, A. M., Morales, J., Sánchez-Zapata, J. A., and Sebastián, E., Spatial Bayesian modelling for studying waterbird biodiversity in artificial ponds of the Vega Baja (Spain)

• Broner S. and Delicado P., Spatial data analysis for 2004 electoral data in Barcelona

• Cerneková, K. and Stehlík, M., D-optimal spatial designs recovering of Dark Age Crete

• Comas, C. and Mateu, J., Space-time dynamics of reproducing cells

• Dabo-Niang, S. and Yao, A. F., Nonparametric regression estimation and prediction for spatial processes

• El Adlouni, S. and Ouarda, T.B.M.J., Fully Bayesian inference of the non-stationary GEV model

• Escaramís, G., Ascaso, C., Abellana, R., Aponte, J. J., Nhacolo, A., Nhalungo, D., and Alonso P., Spatial analysis of variation in time trends of children under 5 mortality in Manhiça (Mozambique)

• Esnaola, S., Montoya, I., Calvo, M., Ibáñez, B., Aldasoro, E., Ruiz, R., and Audicana, C., Geographic variation of mortality risk in the Basque Country

• Febrero, M., Galeano, P., and González-Manteiga, W., Outliers detection for functional data by depth measures

• Fernández-Pascual, R., Ruiz-Medina, M. D., and Angulo, J. M., Functional inverse extrapolation and filtering in space and time

• Frías , M. P., Ruiz-Medina, M. D., Angulo, J. M., and Alonso, F. J., Different estimation methods of spatiotemporal strong dependence with anisotropy

• García-Soidán, P., Modelling spatial dependence using kernel variogram estimators

• Gautherat, E. and Gayraud, G., Parametric estimation in noisy blind deconvolution system: a new estimation procedure

• Giraldo, R., Design of a sampling network for an estuary in the colombian caribbean, using geostatistical methods

• Gómez-Rubio, V., Best, N., and Richardson, S., Bayesian methods for small area estimation using spatio-temporal models

• Horová, I., Forbelská, M., and Zelinka, J., Comparative Study of the Estimation of the Area Under the ROC Curves

• Ibáñez, B., Ugarte, M.D., and Militino, A.F, Spatio-temporal modelling in disease mapping

• Ibáñez, M. V., A first approach to a dynamic modelling

• Kojima, H., A contextual analysis of allergies in Japan, drawing on the JGSS-2002 micro-data and the PRTR macro-data

• Lahuerta-Marin, A., Williams, N. J., Jones, T. R., Begon, M. E., Hart, C. A., and Bennett, M., Cross sectional study of enteric pathogens in wildlife and cattle in Cheshire (UK)

• Lauridsen, J., Bech, M., López, F., and Maté Sánchez, M, A spatiotemporal analysis of public pharmaceutical expenditures

• Martínez-Beneito, M. A., López-Quílez, A. and Botella-Rocamora, P., Autoregressive spatio-temporal disease mapping

• Martos, C., Saez, M., Saurina, C., Lertxundi - Manterola, A., Alcalá, T., and Arribas, F., An 'excess zero' problem in complex data structures in the geographical variation of stomach and testicle cancer in Girona and Zaragoza, Spain

• Menezes, R. and Diggle, P., Geostatistical analysis under preferential sampling

• Mohammadian Mosamam, A. and Kent, J. T., Coherence and spatial temporal processes

• Montero-Lorenzo, J. M. and Larraz-Iribas, B., Cokriging versus univariate interpolation methods: An application to the premises market

• Nordman, D., An empirical likelihood method for variogram estimation

• Palacios, M. B. and Steel, M. F. J., Bayesian Geostatistical Modelling: Gaussian versus non-Gaussian models

• Perrin, O., Self-similarity and Lamperti transformation for random fields

• Peyrard, N., Allard, D., and Forbes, F., How to classify point-referenced data using the EM algorithm?

• Porcu, E., Nicolis, O., and Mateu, J., Decoupling of local and global behaviour for the Dagum random field and related models

• Ruiz-Gazen, A. and Thomas-Agnan, C., Exploratory spatial data analysis with the R package GeoXp

• Schmid, V., Whitcher, B., and Yang, G. Z., A Bayesian hierarchical framework for pharmacokinetic modelling in dynamic contrast-enhanced magnetic resonance cancer imaging

• Silva, G. L. and Dean, C. B., Bayesian spatiotemporal analysis of revascularization odds using splines

• Trívez, J. and Mur, J., Temporal and spatial elements in regional employment models. The Spanish case