1. Introduction to geostatistics. Basic concepts. Spatial autocorrelation.
2. Random Function, Regionalized Variable.
3. Global and local interpolation techniques, exact and inexact interpolator. Deterministic methods.
4. Stationarity and intrinsic hypothesis. Basic geostatistical tool for measuring spatial autocorrelation of a regionalized variable.
5. Variogram. Experimental variogram. Range and anizotropy. Regularized and deregularized semivariogram model. Covariation.
6. Trends in geostatistics - polynomial, global, local.
7. Spatially continuous data analysis. Kriging. Simple, ordinary, universal kriging.
8. Spatially continuous data analysis. Indicator kriging, probability kriging.
9. Spatially continuous data analysis. Co-kriging.
10. Cross validation approaches. Error assessment.
11. Empirical Bayesian kriging.
12. Nonlinear kriging methods.
13. Geostatistic conditional simulation.
2. Random Function, Regionalized Variable.
3. Global and local interpolation techniques, exact and inexact interpolator. Deterministic methods.
4. Stationarity and intrinsic hypothesis. Basic geostatistical tool for measuring spatial autocorrelation of a regionalized variable.
5. Variogram. Experimental variogram. Range and anizotropy. Regularized and deregularized semivariogram model. Covariation.
6. Trends in geostatistics - polynomial, global, local.
7. Spatially continuous data analysis. Kriging. Simple, ordinary, universal kriging.
8. Spatially continuous data analysis. Indicator kriging, probability kriging.
9. Spatially continuous data analysis. Co-kriging.
10. Cross validation approaches. Error assessment.
11. Empirical Bayesian kriging.
12. Nonlinear kriging methods.
13. Geostatistic conditional simulation.