R: Spatial Predictive Modeling

# Spatial Predictive Modeling

## Documentation for package ‘spm’ version 1.2.3

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

avi | Averaged variable importance based on random forest
cran-comments | Note on notes
gbmcv | Cross validation, n-fold for generalized boosted regression modeling (gbm)
gbmidwcv | Cross validation, n-fold for the hybrid method of generalized boosted regression modeling and inverse distance weighting (gbmidw)
gbmidwpred | Generate spatial predictions using the hybrid method of generalized boosted regression modeling and inverse distance weighting (gbmidw)
gbmokcv | Cross validation, n-fold for the hybrid method of generalized boosted regression modeling and ordinary kriging (gbmok)
gbmokgbmidwcv | Cross validation, n-fold for the average of the hybrid method of generalized boosted regression modeling and ordinary kriging and the hybrid method of generalized boosted regression modeling and inverse distance weighting (gbmokgbmidw)
gbmokgbmidwpred | Generate spatial predictions using the average of the hybrid method of generalized boosted regression modeling and ordinary kriging and the hybrid method of generalized boosted regression modeling and inverse distance weighting (gbmokgbmidw)
gbmokpred | Generate spatial predictions using the hybrid method of generalized boosted regression modeling and ordinary kriging (gbmok)
gbmpred | Generate spatial predictions using generalized boosted regression modeling ('gbm')
hard | A dataset of seabed hardness in the eastern Joseph Bonaparte Golf, northern Australia marine margin
idwcv | Cross validation, n-fold for inverse distance weighting (IDW)
idwpred | Generate spatial predictions using inverse distance weighting (IDW)
okcv | Cross validation, n-fold for ordinary kriging (OK)
okpred | Generate spatial predictions using ordinary kriging (OK)
petrel | A dataset of seabed sediments in the Petrel sub-basin in Australia Exclusive Economic Zone
petrel.grid | A dataset of grids for producing spatial predictions of seabed sediment content in the Petrel sub-basin in Australia Exclusive Economic Zone
pred.acc | Predictive error and accuracy measures for predictive models based on cross-validation
RFcv | Cross validation, n-fold for random forest (RF)
rfidwcv | Cross validation, n-fold for the hybrid method of random forest and inverse distance weighting (RFIDW)
rfidwpred | Generate spatial predictions using the hybrid method of random forest and inverse distance weighting (RFIDW)
rfokcv | Cross validation, n-fold for the hybrid method of random forest and ordinary kriging (RFOK)
rfokpred | Generate spatial predictions using the hybrid method of random forest and ordinary kriging (RFOK)
rfokrfidwcv | Cross validation, n-fold for the average of the hybrid method of random forest and ordinary kriging and the hybrid method of random forest and inverse distance weighting (RFOKRFIDW)
rfokrfidwpred | Generate spatial predictions using the average of the hybrid method of random forest and ordinary kriging and the hybrid method of random forest and inverse distance weighting (RFOKRFIDW)
rfpred | Generate spatial predictions using random forest (RF)
rgcv | Cross validation, n-fold for random forest in ranger (RG)
rgidwcv | Cross validation, n-fold for the hybrid method of random forest in ranger and inverse distance weighting (RGIDW)
rgidwpred | Generate spatial predictions using the hybrid method of random forest in ranger and inverse distance weighting (RGIDW)
rgokcv | Cross validation, n-fold for the hybrid method of random forest in ranger and ordinary kriging (RGFOK)
rgokpred | Generate spatial predictions using the hybrid method of random forest in ranger and ordinary kriging (RGOK)
rgokrgidwcv | Cross validation, n-fold for the average of the hybrid method of random forest in ranger (RG) and ordinary kriging and the hybrid method of RG and inverse distance weighting (RGOKRGIDW)
rgokrgidwpred | Generate spatial predictions using the average of the hybrid method of random forest in ranger (RG) and ordinary kriging and the hybrid method of RG and inverse distance weighting (RGOKRGIDW)
rgpred | Generate spatial predictions using random forest in ranger (RG)
rvi | Relative variable influence based on generalized boosted regression modeling (gbm)
sponge | A dataset of sponge species richness in the Timor Sea region, northern Australia marine margin
sponge.grid | A dataset of predictors for generating sponge species richness in a selected region in the Timor Sea region, northern Australia marine margin
sw | A dataset of grids for producing spatial predictions of seabed mud content in the southwest Australia Exclusive Economic Zone
swmud | A dataset of seabed mud content in the southwest Australia Exclusive Economic Zone
tovecv | Convert error measures to vecv
vecv | Variance explained by predictive models based on cross-validation