spm21.1.3 package

Spatial Predictive Modeling

ccr

Correct classification rate for predictive models based on cross -vali...

cran-comments

Note on notes

datasplit

Split data for k-fold cross-validation

decimaldigit

Digit number after decimal point for a numeric variable

gbmkrigeidwcv

Cross validation, n-fold and leave-one-out for the hybrid methods of g...

gbmkrigeidwpred

Generate spatial predictions using the hybrid methods of generalized b...

glmcv

Cross validation, n-fold and leave-one-out for generalised linear mode...

glmidwcv

Cross validation, n-fold and leave-one-out for the hybrid method of ge...

glmidwpred

Generate spatial predictions using the hybrid method of generalised li...

glmkrigecv

Cross validation, n-fold and leave-one-out for the hybrid method of ge...

glmkrigeidwcv

Cross validation, n-fold and leave-one-out for the hybrid methods of g...

glmkrigeidwpred

Generate spatial predictions using the hybrid methods of generalised l...

glmkrigepred

Generate spatial predictions using the hybrid method of generalised li...

glmnetcv

Cross validation, n-fold and leave-one-out, for 'glmnet' in 'glmnet' p...

glmpred

Generate spatial predictions using generalised linear models ('glm')

glscv

Cross validation, n-fold and leave-one-out for generalized least squar...

glsidwcv

Cross validation, n-fold and leave-one-out for the hybrid method of ge...

glsidwpred

Generate spatial predictions using the hybrid method of generalized le...

glskrigecv

Cross validation, n-fold and leave-one-out for the hybrid method of ge...

glskrigeidwcv

Cross validation, n-fold and leave-one-out for the hybrid methods of g...

glskrigeidwpred

Generate spatial predictions using the hybrid methods of generalised l...

glskrigepred

Generate spatial predictions using the hybrid method of generalized le...

glspred

Generate spatial predictions using generalized least squares ('gls')

krigecv

Cross validation, n-fold and leave-one-out for kriging methods ('krige...

krigepred

Generate spatial predictions using kriging methods ('krige')

rfkrigeidwcv

Cross validation, n-fold and leave-one-out for the hybrid methods of '...

rfkrigeidwpred

Generate spatial predictions using the hybrid methods of 'random fores...

svmcv

Cross validation, n-fold and leave-one-out for support vector machine ...

svmidwcv

Cross validation, n-fold and leave-one-out for the hybrid method of su...

svmidwpred

Generate spatial predictions using the hybrid method of support vector...

svmkrigecv

Cross validation, n-fold and leave-one-out for the hybrid method of su...

svmkrigeidwcv

Cross validation, n-fold and leave-one-out for the hybrid methods of s...

svmkrigeidwpred

Generate spatial predictions using the hybrid methods of support vecto...

svmkrigepred

Generate spatial predictions using the hybrid method of support vector...

svmpred

Generate spatial predictions using support vector machine ('svm')

tpscv

Cross validation, n-fold and leave-one-out for thin plate splines ('TP...

An updated and extended version of 'spm' package, by introducing some further novel functions for modern statistical methods (i.e., generalised linear models, glmnet, generalised least squares), thin plate splines, support vector machine, kriging methods (i.e., simple kriging, universal kriging, block kriging, kriging with an external drift), and novel hybrid methods (228 hybrids plus numerous variants) of modern statistical methods or machine learning methods with mathematical and/or univariate geostatistical methods for spatial predictive modelling. For each method, two functions are provided, with one function for assessing the predictive errors and accuracy of the method based on cross-validation, and the other for generating spatial predictions. It also contains a couple of functions for data preparation and predictive accuracy assessment.

  • Maintainer: Jin Li
  • License: GPL (>= 2)
  • Last published: 2023-04-06