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spup  

Spatial Uncertainty Propagation Analysis
View on CRAN: Click here


Download and install spup package within the R console
Install from CRAN:
install.packages("spup")

Install from Github:
library("remotes")
install_github("cran/spup")

Install by package version:
library("remotes")
install_version("spup", "1.4-0")



Attach the package and use:
library("spup")
Maintained by
Kasia Sawicka
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-04-13
Latest Update: 2024-01-10
Description:
Uncertainty propagation analysis in spatial environmentalmodelling 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.
How to cite:
Kasia Sawicka (2017). spup: Spatial Uncertainty Propagation Analysis. R package version 1.4-0, https://cran.r-project.org/web/packages/spup. Accessed 27 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:08), 0.1-0 (2017-04-13 23:21), 0.1-1 (2017-07-24 12:59), 1.2-1 (2018-03-14 17:35), 1.3-1 (2018-07-03 16:20), 1.3-2 (2020-05-01 00:20)
Other packages that cited spup R package
View spup citation profile
Other R packages that spup depends, imports, suggests or enhances
Complete documentation for spup
Functions, R codes and Examples using the spup R package
Some associated functions: OC . OC_sd . TN . TN_sd . check_distribution . check_if_Spatial . crm2vgm . defineMUM . defineUM . dem30m . dem30m_sd . distribution_sampling . distribution_sampling_raster . executable . find_strata . genSample.JointNumericSpatial . genSample.JointScalar . genSample.MarginalCategoricalSpatial . genSample.MarginalNumericSpatial . genSample.MarginalScalar . genSample . list_depth . makeCRM . mean_MC_sgdf . plot.SpatialCorrelogramModel . print.template . propagate . quantile_MC_sgdf . render.character . render . render.template . sd_MC_sgdf . spup--pkg . stratsamp . template . var_MC_sgdf . varcov . vgm2crm . woon . 
Some associated R codes: OC-data.R . OC_sd-data.R . TN-data.R . TN_sd-data.R . check_distribution.R . check_if_Spatial.R . crm2vgm.R . defineUM.R . dem30m-data.R . dem30m_sd-data.R . distribution_sampling.R . distribution_sampling_raster.R . executable.R . find_strata.R . genSample.JointNumericSpatial.R . genSample.JointScalar.R . genSample.MarginalCategoricalSpatial.R . genSample.MarginalNumericSpatial.R . genSample.MarginalScalar.R . genSample.R . list_depth.R . makeCRM.R . mean_MC_sgdf.R . plot.SpatialCorrelogramModel.R . print.template.R . propagate.R . quantile_MC_sgdf.R . render.R . render.character.R . render.template.R . sd_MC_sgdf.R . spup.R . stratsamp.R . template.R . var_MC_sgdf.R . varcov.R . vgm2crm.R . woon-data.R .  Full spup package functions and examples
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