Package: spup 1.4-0

spup: Spatial Uncertainty Propagation Analysis

Uncertainty propagation analysis in spatial environmental modelling following methodology described in Heuvelink et al. (2007) <doi:10.1080/13658810601063951> and Brown and Heuvelink (2007) <doi:10.1016/j.cageo.2006.06.015>. 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.

Authors:Kasia Sawicka [aut, cre], Gerard Heuvelink [aut], Dennis Walvoort [aut], Stefan van Dam [ctb], Damiano Luzzi [ctb]

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spup.pdf |spup.html
spup/json (API)
NEWS

# Install 'spup' in R:
install.packages('spup', repos = c('https://ksawicka.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ksawicka/spup/issues

Datasets:
  • OC - Soil organic carbon content in a south area (33 x 33km) of lake Alaotra in Madagascar.
  • OC_sd - Standard deviation of soil organic carbon content in a south area (33 x 33km) of lake Alaotra in Madagascar.
  • TN - Soil total nitrogen content in a south area (33 x 33km) of lake Alaotra in Madagascar.
  • TN_sd - Standard deviation of soil total nitrogen content in a south area (33 x 33km) of lake Alaotra in Madagascar.
  • dem30m - Digital Elevation Model of Zlatibor region in Serbia.
  • dem30m_sd - Standard deviation of Digital Elevation Model of Zlatibor region in Serbia.
  • woon - Neighbourhood in Rotterdam.

On CRAN:

monte-carlospatialuncertainty-analysisuncertainty-propagation

6.31 score 9 stars 57 scripts 183 downloads 14 exports 34 dependencies

Last updated 11 months agofrom:f6434a87a2. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-winOKNov 12 2024
R-4.5-linuxOKNov 12 2024
R-4.4-winOKNov 12 2024
R-4.4-macOKNov 12 2024
R-4.3-winOKNov 12 2024
R-4.3-macOKNov 12 2024

Exports:defineMUMdefineUMexecutablegenSamplelist_depthmakeCRMmean_MC_sgdfpropagatequantile_MC_sgdfrendersd_MC_sgdftemplatevar_MC_sgdfvarcov

Dependencies:abindclassclassIntcliDBIe1071FNNgluegstatintervalsKernSmoothlatticelifecyclemagrittrMASSmvtnormproxypurrrrasterRcpprlangs2sfsftimespspacetimestarsterraunitsvctrswhiskerwkxtszoo

Spatial Uncertainty Propagation Analysis

Rendered fromExternalModel_v2.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2018-07-17
Started: 2017-04-03

Spatial Uncertainty Propagation Analysis

Rendered fromRotterdam.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2018-07-17
Started: 2017-01-30

Spatial Uncertainty Propagation Analysis

Rendered fromCN_v2.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2018-07-17
Started: 2017-06-15

Spatial Uncertainty Propagation Analysis

Rendered fromDEM_v3.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2018-07-17
Started: 2017-02-08

Readme and manuals

Help Manual

Help pageTopics
Simple check if distribution provided in defineUM() belongs to a list of supported distributions.check_distribution
Simple check if class of provided object is Spatialcheck_if_Spatial
Converting a spatial correlogram model to a variogram modelcrm2vgm
Define Mulivariate Uncertainty ModeldefineMUM
Define an uncertainty model for a single variabledefineUM
Digital Elevation Model of Zlatibor region in Serbia.dem30m
Standard deviation of Digital Elevation Model of Zlatibor region in Serbia.dem30m_sd
Sampling from a given distributiondistribution_sampling
Sampling from a given distributiondistribution_sampling_raster
Wrapper function for calling executables in Rexecutable
Sampling from a given distributionfind_strata
Methods for generating Monte Carlo realizations from uncertain inputs.genSample
Generating Monte Carlo sample from a list of uncertain objects that are cross-correlated.genSample.JointNumericSpatial
Generating sample from cross-correlated variables described by a scalar.genSample.JointScalar
Generating Monte Carlo sample from an uncertain object of a class 'MarginalCategoricalSpatial'genSample.MarginalCategoricalSpatial
Generating Monte Carlo sample from an uncertain object of a class 'MarginalNumericSpatial'genSample.MarginalNumericSpatial
Generating Monte Carlo sample from an uncertain object of a class 'MarginalScalar'genSample.MarginalScalar
Function to find the level of list nestinglist_depth
Defining a spatial correlogram modelmakeCRM makecrm
mean() function for MC sample saved in a SpatialGridDataFramemean_MC_sgdf
Soil organic carbon content in a south area (33 x 33km) of lake Alaotra in Madagascar.OC
Standard deviation of soil organic carbon content in a south area (33 x 33km) of lake Alaotra in Madagascar.OC_sd
Plots correlogram modelplot.SpatialCorrelogramModel
Print method for class "template."print.template
Propagation functionpropagate
quantile() function for MC sample saved in a SpatialGridDataFramequantile_MC_sgdf
Rendering templaterender
Render method for "character" class.render.character
Render method for "template" class.render.template
sd() function for MC sample saved in a SpatialGridDataFramesd_MC_sgdf
spup - Package for spatial uncertainty propagationspup--pkg _PACKAGE
Stratified sampling for spatial variablesstratsamp
Constructor for class "template".template
Soil total nitrogen content in a south area (33 x 33km) of lake Alaotra in Madagascar.TN
Standard deviation of soil total nitrogen content in a south area (33 x 33km) of lake Alaotra in Madagascar.TN_sd
var() function for MC sample saved in a SpatialGridDataFramevar_MC_sgdf
Calculate variance covariance matrixvarcov
Convert vgm to crmvgm2crm
Neighbourhood in Rotterdam.woon