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) .


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install.packages("spm")

1.2.0 by Jin Li, 6 months ago


Browse source code at https://github.com/cran/spm


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