Function reference

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

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

names(<SSN>)

names SSN 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

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