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SSN (version 1.1.4)

Spatial Modeling on Stream Networks

Description

Geostatistical modeling for data on stream networks, including models based on in-stream distance. Models are created using moving average constructions. Spatial linear models, including covariates, can be fit with ML or REML. Mapping and other graphical functions are included.

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Version

Install

install.packages('SSN')

Monthly Downloads

58

Version

1.1.4

License

GPL-2

Maintainer

Jay Hoef

Last Published

November 4th, 2014

Functions in SSN (1.1.4)

Torgegram

Empirical Semivariogram Based on Hydrologic Distance and flow connection
fitSimPoi

Fitted glmssn object for simulated data
importSSN

Import an object of class SpatialStreamNetwork
influenceSSN-class

Class "influenceSSN"
SSN-package

Spatial Modeling on Stream Networks
residuals.glmssn

Compute Model Residuals for glmssn Objects
fitSimGau

Fitted glmssn object for simulated data
plot.glmssn.predict

Plot glmssn.predict Objects
fitSpRE2

Fitted glmssn object for example data set MiddleFork.ssn
fitNS

Fitted glmssn object for example data set MiddleFork.ssn
putSSNdata.frame

putSSNdata.frame
fitRE

Fitted glmssn object for example data set MiddleFork.ssn
SpatialStreamNetwork-class

Class "SpatialStreamNetwork"
createDistMat

Calculate Hydrologic Distances for a SpatialStreamNetwork Object
updatePath

Update Path Slot in SpatialStreamNetwork Object
covparms

Get Covariance Parameters
fitSpRE1

Fitted glmssn object for example data set MiddleFork.ssn
mf04

imported SpatialStreamNetwork object from MiddleFork04.ssn data folder
plot.influenceSSN

Plotting Method for influenceSSN Objects
plot.SpatialStreamNetwork

Plotting Method for SpatialStreamNetwork Objects
BLUP

Compute the joint mean, variance and covariance of any random effects in a glmssn model conditional on the data
BlockPredict

Block Predicton for Streams Data
importPredpts

Import Prediction Points into a SpatialStreamNetwork or glmssn Object
splitPredictions

Split Prediction Sets in a SpatialStreamNetwork Object
mf04p

Imported SpatialStreamNetwork object from MiddleFork04.ssn data folder
CrossValidationSSN

Compute Crossvalidation Values for glmssn Objects
SimulateOnSSN

Simulating Data on Spatial Stream Networks
print.summary.glmssn

Print summary - S3 Method for Class 'glmssn'
AIC

AIC for glmssn objects
CrossValidationStatsSSN

Compute Summary Statistics on Crossvalidation Values for glmssn Objects
binSp

Fitted glmssn object for example data set MiddleFork.ssn
boxplot.SpatialStreamNetwork

Box-and-whisker plots for data within SpatialStreamNetwork objects.
additive.function

Generate an Additive Function Value
subsetSSN

Subset a SpatialStreamNetwork Object
getPreds

Extract Predictions with associated standard errors.
plot.Torgegram

Plotting Method for Torgegram Objects
writeSSN

Write a SpatialStreamNetwork Object
InfoCritCompare

Compare glmssn Information Criteria
MiddleFork04.ssn

MiddleFork04.ssn data folder
varcomp

Variance Components for glmssn Objects
GR2

Generalised R2
fitSpBk

Fitted glmssn object for example data set MiddleFork.ssn
predict.glmssn

Calculate Predictions for Prediction Sites
EmpiricalSemivariogram

Empirical Semivariogram Based on Euclidean Distance
Design functions

Design functions
summary.glmssn

Summary - S3 Method for Class 'glmssn'
glmssn-class

Class "glmssn"
createSSN

Create an SpatialStreamnetwork Object
fitSp

Fitted glmssn object for example data set MiddleFork.ssn
fitSimBin

Fitted glmssn object for simulated data
poiSp

Fitted glmssn object for example data set MiddleFork.ssn
glmssn

Fitting Generalized Linear Models for Spatial Stream Networks