Spatial Predictive Modeling

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Documentation for package ‘spm’ version 1.2.2

• 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