R: Spatial Modeling on Stream Networks

# Spatial Modeling on Stream Networks

## Documentation for package ‘SSN2’ version 0.4.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A C D E F G H I L M N P R S T V

## -- A --

amongSitesBigDistMat | Helper function to determining distance matrices among sites
anova.SSN2 | Compute analysis of variance and likelihood ratio tests of fitted model objects
anova.ssn_glm | Compute analysis of variance and likelihood ratio tests of fitted model objects
anova.ssn_lm | Compute analysis of variance and likelihood ratio tests of fitted model objects
augment.SSN2 | Augment data with information from fitted model objects
augment.ssn_glm | Augment data with information from fitted model objects
augment.ssn_lm | Augment data with information from fitted model objects

## -- C --

coef.SSN2 | Extract fitted model coefficients
coef.ssn_glm | Extract fitted model coefficients
coef.ssn_lm | Extract fitted model coefficients
coefficients.ssn_glm | Extract fitted model coefficients
coefficients.ssn_lm | Extract fitted model coefficients
confint.SSN2 | Confidence intervals for fitted model parameters
confint.ssn_glm | Confidence intervals for fitted model parameters
confint.ssn_lm | Confidence intervals for fitted model parameters
cooks.distance.SSN2 | Compute Cook's distance
cooks.distance.ssn_glm | Compute Cook's distance
cooks.distance.ssn_lm | Compute Cook's distance
copy_lsn_to_temp | Copy LSN to temporary directory
covmatrix.SSN2 | Create a covariance matrix
covmatrix.ssn_glm | Create a covariance matrix
covmatrix.ssn_lm | Create a covariance matrix
create_netgeom | Create netgeom column in SSN object

## -- D --

deviance.SSN2 | Fitted model deviance
deviance.ssn_glm | Fitted model deviance
deviance.ssn_lm | Fitted model deviance

## -- E --

euclid_initial | Create a covariance parameter initial object
euclid_params | Create covariance parameter objects.

## -- F --

fitted.SSN2 | Extract model fitted values
fitted.ssn_glm | Extract model fitted values
fitted.ssn_lm | Extract model fitted values
fitted.values.ssn_glm | Extract model fitted values
fitted.values.ssn_lm | Extract model fitted values
formula.SSN2 | Model formulae
formula.ssn_glm | Model formulae
formula.ssn_lm | Model formulae

## -- G --

glance.SSN2 | Glance at a fitted model object
glance.ssn_glm | Glance at a fitted model object
glance.ssn_lm | Glance at a fitted model object
glances.SSN2 | Glance at many fitted model objects
glances.ssn_glm | Glance at many fitted model objects
glances.ssn_lm | Glance at many fitted model objects

## -- H --

hatvalues.SSN2 | Compute leverage (hat) values
hatvalues.ssn_glm | Compute leverage (hat) values
hatvalues.ssn_lm | Compute leverage (hat) values

## -- I --

influence.SSN2 | Regression diagnostics
influence.ssn_glm | Regression diagnostics
influence.ssn_lm | Regression diagnostics

## -- L --

labels.SSN2 | Find labels from object
labels.ssn_glm | Find labels from object
labels.ssn_lm | Find labels from object
logLik.SSN2 | Extract log-likelihood
logLik.ssn_glm | Extract log-likelihood
logLik.ssn_lm | Extract log-likelihood
loocv.SSN2 | Perform leave-one-out cross validation
loocv.ssn_glm | Perform leave-one-out cross validation
loocv.ssn_lm | Perform leave-one-out cross validation

## -- M --

mf04p | Imported SSN object from the MiddleFork04.ssn data folder
MiddleFork04.ssn | MiddleFork04.ssn: Middle Fork 2004 stream temperature dataset
model.frame.SSN2 | Extract the model frame from a fitted model object
model.frame.ssn_glm | Extract the model frame from a fitted model object
model.frame.ssn_lm | Extract the model frame from a fitted model object
model.matrix.SSN2 | Extract the model matrix from a fitted model object
model.matrix.ssn_glm | Extract the model matrix from a fitted model object
model.matrix.ssn_lm | Extract the model matrix from a fitted model object

## -- N --

nugget_initial | Create a covariance parameter initial object
nugget_params | Create covariance parameter objects.

## -- P --

plot.SSN2 | Plot fitted model diagnostics
plot.ssn_glm | Plot fitted model diagnostics
plot.ssn_lm | Plot fitted model diagnostics
plot.Torgegram | Plot Torgegram
predict.SSN2 | Model predictions (Kriging)
predict.ssn_glm | Model predictions (Kriging)
predict.ssn_lm | Model predictions (Kriging)
print.anova.ssn_glm | Print values
print.anova.ssn_lm | Print values
print.SSN | Print SSN object
print.SSN2 | Print values
print.ssn_glm | Print values
print.ssn_lm | Print values
print.summary.ssn_glm | Print values
print.summary.ssn_lm | Print values
pseudoR2.SSN2 | Compute a pseudo r-squared
pseudoR2.ssn_glm | Compute a pseudo r-squared
pseudoR2.ssn_lm | Compute a pseudo r-squared

## -- R --

resid.ssn_glm | Extract fitted model residuals
resid.ssn_lm | Extract fitted model residuals
residuals.SSN2 | Extract fitted model residuals
residuals.ssn_glm | Extract fitted model residuals
residuals.ssn_lm | Extract fitted model residuals
rstandard.ssn_glm | Extract fitted model residuals
rstandard.ssn_lm | Extract fitted model residuals

## -- S --

ssn_create_bigdist | Calculate Hydrologic Distances for an 'SSN' object
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
ssn_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
ssn_params | Create covariance parameter objects.
ssn_put_data | Put an sf data.frame in an SSN object
ssn_rbeta | Simulate random variables on a stream network
ssn_rbinom | Simulate random variables on a stream network
ssn_rgamma | Simulate random variables on a stream network
ssn_rinvgauss | Simulate random variables on a stream network
ssn_rnbinom | Simulate random variables on a stream network
ssn_rnorm | Simulate random variables on a stream network
ssn_rpois | Simulate random variables on a stream network
ssn_simulate | 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.SSN2 | Summarize a fitted model object
summary.ssn_glm | Summarize a fitted model object
summary.ssn_lm | Summarize a fitted model object

## -- T --

taildown_initial | Create a covariance parameter initial object
taildown_params | Create covariance parameter objects.
tailup_initial | Create a covariance parameter initial object
tailup_params | Create covariance parameter objects.
tidy.anova.ssn_glm | Compute analysis of variance and likelihood ratio tests of fitted model objects
tidy.anova.ssn_lm | Compute analysis of variance and likelihood ratio tests of fitted model objects
tidy.SSN2 | Tidy a fitted model object
tidy.ssn_glm | Tidy a fitted model object
tidy.ssn_lm | Tidy a fitted model object
Torgegram | Compute the empirical semivariogram

## -- V --

varcomp.SSN2 | Variability component comparison
varcomp.ssn_glm | Variability component comparison
varcomp.ssn_lm | Variability component comparison
vcov.SSN2 | Calculate variance-covariance matrix for a fitted model object
vcov.ssn_glm | Calculate variance-covariance matrix for a fitted model object
vcov.ssn_lm | Calculate variance-covariance matrix for a fitted model object