Function reference • SSN2

All functions
`AIC(<ssn_lm>)` `AIC(<ssn_glm>)` `AICc(<ssn_lm>)` `AICc(<ssn_glm>)`	Compute AIC and AICc of fitted model objects
`anova(<ssn_lm>)` `anova(<ssn_glm>)` `tidy(<anova.ssn_lm>)` `tidy(<anova.ssn_glm>)`	Compute analysis of variance and likelihood ratio tests of fitted model objects
`augment(<ssn_lm>)` `augment(<ssn_glm>)`	Augment data with information from fitted model objects
`coef(<ssn_lm>)` `coefficients(<ssn_lm>)` `coef(<ssn_glm>)` `coefficients(<ssn_glm>)`	Extract fitted model coefficients
`confint(<ssn_lm>)` `confint(<ssn_glm>)`	Confidence intervals for fitted model parameters
`cooks.distance(<ssn_lm>)` `cooks.distance(<ssn_glm>)`	Compute Cook's distance
`copy_lsn_to_temp()`	Copy LSN to temporary directory
`covmatrix(<ssn_lm>)` `covmatrix(<ssn_glm>)`	Create a covariance matrix
`create_netgeom()`	Create netgeom column in SSN object
`deviance(<ssn_lm>)` `deviance(<ssn_glm>)`	Fitted model deviance
`fitted(<ssn_lm>)` `fitted.values(<ssn_lm>)` `fitted(<ssn_glm>)` `fitted.values(<ssn_glm>)`	Extract model fitted values
`formula(<ssn_lm>)` `formula(<ssn_glm>)`	Model formulae
`glance(<ssn_lm>)` `glance(<ssn_glm>)`	Glance at a fitted model object
`glances(<ssn_lm>)` `glances(<ssn_glm>)`	Glance at many fitted model objects
`hatvalues(<ssn_lm>)` `hatvalues(<ssn_glm>)`	Compute leverage (hat) values
`influence(<ssn_lm>)` `influence(<ssn_glm>)`	Regression diagnostics
`labels(<ssn_lm>)` `labels(<ssn_glm>)`	Find labels from object
`logLik(<ssn_lm>)` `logLik(<ssn_glm>)`	Extract log-likelihood
`loocv(<ssn_lm>)` `loocv(<ssn_glm>)`	Perform leave-one-out cross validation
`mf04p`	Imported SSN object from the MiddleFork04.ssn data folder
`MiddleFork04.ssn`	MiddleFork04.ssn: Middle Fork 2004 stream temperature dataset
`model.frame(<ssn_lm>)` `model.frame(<ssn_glm>)`	Extract the model frame from a fitted model object
`model.matrix(<ssn_lm>)` `model.matrix(<ssn_glm>)`	Extract the model matrix from a fitted model object
`plot(<ssn_lm>)` `plot(<ssn_glm>)`	Plot fitted model diagnostics
`plot(<Torgegram>)`	Plot Torgegram
`predict(<ssn_lm>)` `predict(<ssn_glm>)`	Model predictions (Kriging)
`print(<SSN>)`	Print SSN object
`print(<ssn_lm>)` `print(<ssn_glm>)` `print(<summary.ssn_lm>)` `print(<summary.ssn_glm>)` `print(<anova.ssn_lm>)` `print(<anova.ssn_glm>)`	Print values
`pseudoR2(<ssn_lm>)` `pseudoR2(<ssn_glm>)`	Compute a pseudo r-squared
`residuals(<ssn_lm>)` `resid(<ssn_lm>)` `rstandard(<ssn_lm>)` `residuals(<ssn_glm>)` `resid(<ssn_glm>)` `rstandard(<ssn_glm>)`	Extract fitted model residuals
`ssn_create_distmat()`	Calculate Hydrologic Distances for an `SSN` object
`ssn_get_data()`	Get a data.frame from an SSN, ssn_lm, or ssn_glm object
`ssn_get_netgeom()`	Extract netgeom column
`ssn_get_stream_distmat()`	Get stream distance matrices from an `SSN` object
`ssn_glm()`	Fitting Generalized Linear Models for Spatial Stream Networks
`ssn_import()`	Import `SSN` object
`ssn_import_predpts()`	Import prediction points into an SSN, ssn_lm, or ssn_glm object
`tailup_initial()` `taildown_initial()` `euclid_initial()` `nugget_initial()`	Create a covariance parameter initial object
`ssn_lm()`	Fitting Linear Models for Spatial Stream Networks
`ssn_names()`	Return names of data in an SSN object
`tailup_params()` `taildown_params()` `euclid_params()` `nugget_params()`	Create covariance parameter objects.
`ssn_put_data()`	Put an sf data.frame in an SSN object
`ssn_simulate()` `ssn_rbeta()` `ssn_rbinom()` `ssn_rgamma()` `ssn_rinvgauss()` `ssn_rnbinom()` `ssn_rnorm()` `ssn_rpois()`	Simulate random variables on a stream network
`ssn_split_predpts()`	Split a prediction dataset in an `SSN` object
`ssn_subset()`	Subset an `SSN` object
`SSN_to_SSN2()`	Convert object from `SpatialStreamNetwork` class to `SSN` class
`ssn_update_path()`	Update path in an SSN object
`ssn_write()`	write an SSN object
`summary(<SSN>)`	Summarize an SSN object
`summary(<ssn_lm>)` `summary(<ssn_glm>)`	Summarize a fitted model object
`tidy(<ssn_lm>)` `tidy(<ssn_glm>)`	Tidy a fitted model object
`Torgegram()`	Compute the empirical semivariogram
`varcomp(<ssn_lm>)` `varcomp(<ssn_glm>)`	Variability component comparison
`vcov(<ssn_lm>)` `vcov(<ssn_glm>)`	Calculate variance-covariance matrix for a fitted model object

Reference

All functions