| Center |
| Faculty of Mathematics |
| Departament |
| Statistics and Operational Research |
| Lecturers in charge |
| Sin datos cargados |
| Met. Docent |
| Met. Avaluació |
| Evaluation is composed by three elements: - Proposed exercises during practicum classes (20%). - Final exam on questions (40%). - Applied work with data on a concrete problem (40%). |
| Bibliografia |
| Banerjee, S., Carlin, B.P. y Gelfand, A.E. (2004). Hierarchical Modeling and Analysis for Spatial Data. Chapman & Hall, Boca Raton. Cressie, N. (1993). Statistics for spatial data, segunda edición. John Wiley and Sons, New York. Diggle, P.J. (1983). Statistical analysis of spatial point patterns. Academic Press, London. Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, New York. Ripley, B.D. (1981). Spatial Statistics. John Wiley and Sons, New York. Schabenberger, O. y Gotway, C.A. (2005). Statistics Methods for Spatial Data Analysis. Chapman & Hall, Boca Raton. Waller, L.A. y Gotway, C.A. (2004). Applied Spatial Statistics for Public Health Data. John Wiley and Sons, Hoboken, New Jersey. |
| Continguts |
| Unit I. Introduction Theme 1.- Statistics and the Environment Theme 2.- Generalized Linear Models Unit II. Geostatistics Theme 3.- Stationary continuous processes. Theme 4.- Estimation of the variogram. Theme 5.- Spatial prediction. Unit III. Processes on lattice Theme 6.- Lattice data exploratory analysis. Theme 7.- Markov random fields. Theme 8.- Markov random fields models. Theme 9.- Inference on Markov random fields. Theme 10.- Other Gaussian models. Unit IV. Point patterns Theme 11.- Preliminary exploration. Theme 12.- Point processes. Theme 13.- Point processes models. Theme 14.- Inference on point patterns. Theme 15.- Multivariate point processes. |
| Objetius |
| To identify environmental problems that need a suitable statistical treatment. To develop the aptitude to understand the spatial variability and to understand with statistical terms on real problems, with all its complexity. To differentiate the types of environmental information and to analyze the contexts in which they arise. To assimilate the fundamental steps of the modeling and the statistical analysis of environmental information. To handle computer software for the statistical treatment of spatial observations. To interpret the obtained results in a critical way. |
| URL de Fitxa |
| http://www.uv.es/~antoniol/ |