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SSN (version 1.1.12)

Spatial Modeling on Stream Networks

Description

Spatial statistical modeling and prediction for data on stream networks, including models based on in-stream distance (Ver Hoef, J.M. and Peterson, E.E., 2010. .) Models are created using moving average constructions. Spatial linear models, including explanatory variables, can be fit with (restricted) maximum likelihood. Mapping and other graphical functions are included.

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Version

Install

install.packages('SSN')

Monthly Downloads

125

Version

1.1.12

License

GPL-2

Maintainer

Jay Hoef

Last Published

January 25th, 2018

Functions in SSN (1.1.12)

MiddleFork04.ssn

MiddleFork04.ssn data folder

Spatial Modeling on Stream Networks

InfoCritCompare

Compare glmssn Information Criteria

Block Predicton for Streams Data

CrossValidationSSN

Compute Crossvalidation Values for glmssn Objects

AIC for glmssn objects

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

CrossValidationStatsSSN

Compute Summary Statistics on Crossvalidation Values for glmssn Objects

EmpiricalSemivariogram

Empirical Semivariogram Based on Euclidean Distance

as.SpatialLines

Methods to convert SpatialStreamNetwork objects classes to sp classes

Fitted glmssn object for example data set MiddleFork.ssn

getStreamDistMat

Extract the stream network distance matrix from SSN objects

Fitted glmssn object for simulated data

Fitted glmssn object for simulated data

Extract Predictions with associated standard errors.

getSSNdata.frame

Extract data from SSN objects as a data.frame

Empirical Semivariogram Based on Hydrologic Distance and flow connection

additive.function

Generate an Additive Function Value

Create an SpatialStreamnetwork Object

Simulating Data on Spatial Stream Networks

SpatialStreamNetwork-class

Class "SpatialStreamNetwork"

Fitted glmssn object for example data set MiddleFork.ssn

Fitted glmssn object for example data set MiddleFork.ssn

Design functions

Design functions

Fitted glmssn object for example data set MiddleFork.ssn

getConfusionMat

Extract confusion matrix for binary spatial model predictions.

plot.SpatialStreamNetwork

Plotting Method for SpatialStreamNetwork Objects

Plotting Method for Torgegram Objects

Get Covariance Parameters

Calculate Hydrologic Distances for a SpatialStreamNetwork Object

Fitted glmssn object for example data set MiddleFork.ssn

Fitted glmssn object for example data set MiddleFork.ssn

Import an object of class SpatialStreamNetwork

imported SpatialStreamNetwork object from MiddleFork04.ssn data folder

Imported SpatialStreamNetwork object from MiddleFork04.ssn data folder

Update Path Slot in SpatialStreamNetwork Object

Variance Components for glmssn Objects

influenceSSN-class

Class "influenceSSN"

Fitted glmssn object for example data set MiddleFork.ssn

Calculate Predictions for Prediction Sites

Write a SpatialStreamNetwork Object

Fitting Generalized Linear Models for Spatial Stream Networks

Import Prediction Points into a SpatialStreamNetwork or glmssn Object

Subset a SpatialStreamNetwork Object

Summary - S3 Method for Class 'glmssn'

boxplot.SpatialStreamNetwork

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

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

Fitted glmssn object for simulated data

Fitted glmssn object for example data set MiddleFork.ssn

print.summary.glmssn

Print summary - S3 Method for Class 'glmssn'

putSSNdata.frame

putSSNdata.frame

plot.glmssn.predict

Plot glmssn.predict Objects

plot.influenceSSN

Plotting Method for influenceSSN Objects

residuals.glmssn

Compute Model Residuals for glmssn Objects

splitPredictions

Split Prediction Sets in a SpatialStreamNetwork Object