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SSN (version 1.1.8)

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

1.1.8

License

GPL-2

Maintainer

Jay Hoef

Last Published

October 15th, 2016

Functions in SSN (1.1.8)

Copies the lsn directory MiddleFork04.ssn to R's temporary directory

Fitted glmssn object for example data set MiddleFork.ssn

Block Predicton for Streams Data

boxplot.SpatialStreamNetwork

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

Get Covariance Parameters

AIC for glmssn objects

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

Calculate Hydrologic Distances for a SpatialStreamNetwork Object

Create an SpatialStreamnetwork Object

additive.function

Generate an Additive Function Value

Empirical Semivariogram Using Hydrologic Distance Between Flow-connected Sites

CrossValidationSSN

Compute Crossvalidation Values for glmssn Objects

Fitted glmssn object for example data set MiddleFork.ssn

Empirical Semivariogram Using Hydrologic Distance Between Neighboring Flow-connected Sites

EmpiricalSemivariogram

Empirical Semivariogram Based on Euclidean Distance

CrossValidationStatsSSN

Compute Summary Statistics on Crossvalidation Values for glmssn Objects

Design functions

Design functions

Fitted glmssn object for simulated data

Fitted glmssn object for simulated data

Fitted glmssn object for example data set MiddleFork.ssn

Fitted glmssn object for example data set MiddleFork.ssn

Fitted glmssn object for example data set MiddleFork.ssn

Empirical Semivariogram Using Hydrologic Distance to Nearest Junction Between Flow-unconnected Sites

Fitted glmssn object for example data set MiddleFork.ssn

Extract Predictions with associated standard errors.

Fitted glmssn object for example data set MiddleFork.ssn

Empirical Semivariogram Using Hydrologic Distance Between Flow-unconnected Sites

Fitted glmssn object for simulated data

Fitting Generalized Linear Models for Spatial Stream Networks

Imported SpatialStreamNetwork object from MiddleFork04.ssn data folder

imported SpatialStreamNetwork object from MiddleFork04.ssn data folder

Import an object of class SpatialStreamNetwork

plot.glmssn.predict

Plot glmssn.predict Objects

Import Prediction Points into a SpatialStreamNetwork or glmssn Object

plot.influenceSSN

Plotting Method for influenceSSN Objects

MiddleFork04.ssn

MiddleFork04.ssn data folder

InfoCritCompare

Compare glmssn Information Criteria

influenceSSN-class

Class "influenceSSN"

Find neighboring stream segments

plot.SpatialStreamNetwork

Plotting Method for SpatialStreamNetwork Objects

Fitted glmssn object for example data set MiddleFork.ssn

residuals.glmssn

Compute Model Residuals for glmssn Objects

putSSNdata.frame

putSSNdata.frame

print.summary.glmssn

Print summary - S3 Method for Class 'glmssn'

Simulating Data on Spatial Stream Networks

SpatialStreamNetwork-class

Class "SpatialStreamNetwork"

Plotting Method for Torgegram Objects

Calculate Predictions for Prediction Sites

Subset a SpatialStreamNetwork Object

splitPredictions

Split Prediction Sets in a SpatialStreamNetwork Object

Write a SpatialStreamNetwork Object

Summary - S3 Method for Class 'glmssn'

Variance Components for glmssn Objects

Empirical Semivariogram Based on Hydrologic Distance and flow connection

Spatial Modeling on Stream Networks

Update Path Slot in SpatialStreamNetwork Object