Spatial Predictive Modeling

Introduction to some novel accurate hybrid methods of geostatistical and machine learning methods for spatial predictive modelling. It contains two commonly used geostatistical methods, two machine learning methods, four hybrid methods and two averaging methods. For each method, two functions are provided. One function is for assessing the predictive errors and accuracy of the method based on cross-validation. The other one is for generating spatial predictions using the method. For details please see: Li, J., Potter, A., Huang, Z., Daniell, J. J. and Heap, A. (2010) Li, J., Heap, A. D., Potter, A., Huang, Z. and Daniell, J. (2011) Li, J., Heap, A. D., Potter, A. and Daniell, J. (2011) Li, J., Potter, A., Huang, Z. and Heap, A. (2012) .


Reference manual

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1.2.0 by Jin Li, 2 years ago

Browse source code at

Authors: Jin Li [aut, cre]

Documentation:   PDF Manual  

Task views: Analysis of Spatial Data

GPL (>= 2) license

Imports gstat, sp, randomForest, psy, gbm, biomod2, stats, ranger

Suggests knitr, rmarkdown

See at CRAN