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spup

R package: spup - Spatial Uncertainty Propagation Analysis

Description

Uncertainty propagation analysis in spatial environmental modelling following methodology described in Heuvelink et al. (2007) and Brown and Heuvelink (2007). The package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model outputs. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is accommodated for. The MC realizations may be used as input to the environmental models called from R, or externally.

Installation

R package spup is available on CRAN and can be installed in R as:

install.packages("spup")

The development version from GitHub can be install via:

library(devtools)
install_github("ksawicka/spup")

References

Brown, J. D. and G. B. M. Heuvelink (2007). "The Data Uncertainty Engine (DUE): A software tool for assessing and simulating uncertain environmental variables." Computers & Geosciences 33(2): 172-190.

Heuvelink, G. B. M., et al. (2007). "A probabilistic framework for representing and simulating uncertain environmental variables." International Journal of Geographical Information Science 21(5): 497-513.

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Version

Install

install.packages('spup')

Monthly Downloads

140

Version

1.2-1

License

GPL (>= 3)

Maintainer

Kasia Sawicka

Last Published

March 14th, 2018

Functions in spup (1.2-1)

check_if_Spatial

Simple check if class of provided object is Spatial

Print method for class "template."

Neighbourhood in Rotterdam.

Define an uncertainty model for a single variable

Digital Elevation Model of Zlatibor region in Serbia.

genSample.JointScalar

Generating sample from cross-correlated variables described by a scalar.

genSample.MarginalCategoricalSpatial

Generating Monte Carlo sample from an uncertain object of a class 'MarginalCategoricalSpatial'

Function to find the level of list nesting

Methods for generating Monte Carlo realizations from uncertain inputs.

render.template

Render method for "template" class.

sd() function for MC sample saved in a SpatialGridDataFrame

Soil organic carbon content in a south area (33 x 33km) of lake Alaotra in Madagascar.

Standard deviation of soil organic carbon content in a south area (33 x 33km) of lake Alaotra in Madagascar.

genSample.MarginalNumericSpatial

Generating Monte Carlo sample from an uncertain object of a class 'MarginalNumericSpatial'

genSample.MarginalScalar

Generating Monte Carlo sample from an uncertain object of a class 'MarginalScalar'

Rendering template

render.character

Render method for "character" class.

spup - Package for spatial uncertainty propagation

Stratified sampling for spatial variables

Converting a spatial correlogram model to a variogram model

Define Mulivariate Uncertainty Model

Sampling from a given distribution

genSample.JointNumericSpatial

Generating Monte Carlo sample from a list of uncertain objects that are cross-correlated.

Defining a spatial correlogram model

mean() function for MC sample saved in a SpatialGridDataFrame

Constructor for class "template".

var() function for MC sample saved in a SpatialGridDataFrame

Soil total nitrogen content in a south area (33 x 33km) of lake Alaotra in Madagascar.

Standard deviation of soil total nitrogen content in a south area (33 x 33km) of lake Alaotra in Madagascar.

distribution_sampling_raster

Sampling from a given distribution

Wrapper function for calling executables in R

Propagation function

quantile_MC_sgdf

quantile() function for MC sample saved in a SpatialGridDataFrame

Calculate variance covariance matrix

Convert vgm to crm

check_distribution

Simple check if distribution provided in defineUM() belongs to a list of supported distributions.

Standard deviation of Digital Elevation Model of Zlatibor region in Serbia.

distribution_sampling

Sampling from a given distribution

plot.SpatialCorrelogramModel

Plots correlogram model