Reference

All functions
AICc()	Compute AICc of fitted model objects
anova(<splm>) anova(<spautor>) anova(<spglm>) anova(<spgautor>) tidy(<anova.splm>) tidy(<anova.spautor>) tidy(<anova.spglm>) tidy(<anova.spgautor>)	Compute analysis of variance and likelihood ratio tests of fitted model objects
augment(<splm>) augment(<spautor>) augment(<spglm>) augment(<spgautor>)	Augment data with information from fitted model objects
AUROC()	Area Under Receiver Operating Characteristic Curve
caribou	A caribou forage experiment
coef(<splm>) coefficients(<splm>) coef(<spautor>) coefficients(<spautor>) coef(<spglm>) coefficients(<spglm>) coef(<spgautor>) coefficients(<spgautor>)	Extract fitted model coefficients
confint(<splm>) confint(<spautor>) confint(<spglm>) confint(<spgautor>)	Confidence intervals for fitted model parameters
cooks.distance(<splm>) cooks.distance(<spautor>) cooks.distance(<spglm>) cooks.distance(<spgautor>)	Compute Cook's distance
covmatrix()	Create a covariance matrix
deviance(<splm>) deviance(<spautor>) deviance(<spglm>) deviance(<spgautor>)	Fitted model deviance
dispersion_initial()	Create a dispersion parameter initial object
dispersion_params()	Create a dispersion parameter object
esv() plot(<esv>)	Compute the empirical semivariogram
fitted(<splm>) fitted.values(<splm>) fitted(<spautor>) fitted.values(<spautor>) fitted(<spglm>) fitted.values(<spglm>) fitted(<spgautor>) fitted.values(<spgautor>)	Extract model fitted values
formula(<splm>) formula(<spautor>) formula(<spglm>) formula(<spgautor>)	Model formulae
glance(<splm>) glance(<spautor>) glance(<spglm>) glance(<spgautor>)	Glance at a fitted model object
glances()	Glance at many fitted model objects
hatvalues(<splm>) hatvalues(<spautor>) hatvalues(<spglm>) hatvalues(<spgautor>)	Compute leverage (hat) values
influence(<splm>) influence(<spautor>) influence(<spglm>) influence(<spgautor>)	Regression diagnostics
labels(<splm>) labels(<spautor>) labels(<spglm>) labels(<spgautor>)	Find labels from object
lake	National Lakes Assessment Data
lake_preds	Lakes Prediction Data
logLik(<splm>) logLik(<spautor>) logLik(<spglm>) logLik(<spgautor>)	Extract log-likelihood
loocv()	Perform leave-one-out cross validation
model.frame(<splm>) model.frame(<spautor>) model.frame(<spglm>) model.frame(<spgautor>)	Extract the model frame from a fitted model object
model.matrix(<splm>) model.matrix(<spautor>) model.matrix(<spglm>) model.matrix(<spgautor>)	Extract the model matrix from a fitted model object
moose	Moose counts and presence in Alaska, USA
moose_preds	Locations at which to predict moose counts and presence in Alaska, USA
moss	Heavy metals in mosses near a mining road in Alaska, USA
plot(<splm>) plot(<spautor>) plot(<spglm>) plot(<spgautor>)	Plot fitted model diagnostics
predict(<splm>) predict(<spautor>) predict(<splm_list>) predict(<spautor_list>) predict(<splmRF>) predict(<spautorRF>) predict(<splmRF_list>) predict(<spautorRF_list>) predict(<spglm>) predict(<spgautor>) predict(<spglm_list>) predict(<spgautor_list>)	Model predictions (Kriging)
print(<splm>) print(<spautor>) print(<summary.splm>) print(<summary.spautor>) print(<anova.splm>) print(<anova.spautor>) print(<spglm>) print(<spgautor>) print(<summary.spglm>) print(<summary.spgautor>) print(<anova.spglm>) print(<anova.spgautor>)	Print values
pseudoR2()	Compute a pseudo r-squared
randcov_initial()	Create a random effects covariance parameter initial object
randcov_params()	Create a random effects covariance parameter object
residuals(<splm>) resid(<splm>) rstandard(<splm>) residuals(<spautor>) resid(<spautor>) rstandard(<spautor>) residuals(<spglm>) resid(<spglm>) rstandard(<spglm>) residuals(<spgautor>) resid(<spgautor>) rstandard(<spgautor>)	Extract fitted model residuals
seal	Estimated harbor-seal trends from abundance data in southeast Alaska, USA
spautor()	Fit spatial autoregressive models
spautorRF()	Fit random forest spatial residual models
spcov_initial()	Create a spatial covariance parameter initial object
spcov_params()	Create a spatial covariance parameter object
spgautor()	Fit spatial generalized autoregressive models
spglm()	Fit spatial generalized linear models
splm()	Fit spatial linear models
splmRF()	Fit random forest spatial residual models
sprbeta()	Simulate a spatial beta random variable
sprbinom()	Simulate a spatial binomial random variable
sprgamma()	Simulate a spatial gamma random variable
sprinvgauss()	Simulate a spatial inverse gaussian random variable
sprnbinom()	Simulate a spatial negative binomial random variable
sprnorm()	Simulate a spatial normal (Gaussian) random variable
sprpois()	Simulate a spatial Poisson random variable
sulfate	Sulfate atmospheric deposition in the conterminous USA
sulfate_preds	Locations at which to predict sulfate atmospheric deposition in the conterminous USA
summary(<splm>) summary(<spautor>) summary(<spglm>) summary(<spgautor>)	Summarize a fitted model object
texas	Texas Turnout Data
tidy(<splm>) tidy(<spautor>) tidy(<spglm>) tidy(<spgautor>)	Tidy a fitted model object
varcomp()	Variability component comparison
vcov(<splm>) vcov(<spautor>) vcov(<spglm>) vcov(<spgautor>)	Calculate variance-covariance matrix for a fitted model object