Spatio-Temporal; Inverse Distance Weighting and Radial Basis Functions with Distance-Based Regression


Spatio-temporal: Inverse Distance Weighting (IDW) and radial basis functions; optimization, prediction, summary statistics from leave-one-out cross-validation, adjusting distance-based linear regression model and generation of the principal coordinates of a new individual from Gower's distance.


Package: geosptdb
Type: Package
Version: 0.5-0
Date: 2015-06-22
License: GPL (>= 2)
LazyLoad: yes


Carlos Melo <>, Oscar Melo <

Maintainer: Carlos Melo <>


Cuadras CM, Arenas C, Fortiana J (1996). Some computational aspects of a distance-based model for prediction. Communications in Statistics B - Simulation and Computation 25, 593-609.

Cuadras, CM. and Arenas, C. (1990).A distance-based regression model for prediction with mixed data. Communications in Statistics A - Theory and Methods 19, 2261-2279

Gower, J. C. (1971). A general coefficient of similarity and some of its properties. Biometrics 27:857-871.

Hengl, T. (2009). A Practical Guide to Geostatistical Mapping, 2nd edn, University of Amsterdam, Amsterdam.

Hengl, T., Heuvelink Gerard, B. M., Percec Tadic, M. & Pebesma, E. J. (2012). Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images, Theoretical and Applied Climatology 107, 1-2, 265-277.

Johnston, K., Ver, J., Krivoruchko, K., Lucas, N. 2001. Using ArcGIS Geostatistical Analysis. ESRI.

Melo, C. E. (2012). Analisis geoestadistico espacio tiempo basado en distancias y splines con aplicaciones. PhD. Thesis. Universitat de Barcelona. 276 p. [link]

See Also

rbfST, graph.rbfST, cp.xnews, croatiadb

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