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pMEM: Predictive Moran's Eigenvector Maps

Calculation of Predictive Moran's eigenvector maps (pMEM), as defined by Guénard and Legendre (In Press) "Spatially-explicit predictions using spatial eigenvector maps" <doi:10.5281/zenodo.13356457>. Methods in Ecology and Evolution. This method enables scientists to predict the values of spatially-structured environmental variables. Multiple types of pMEM are defined, each one implemented on the basis of spatial weighting function taking a range parameter, and sometimes also a shape parameter. The code's modular nature enables programers to implement new pMEM by defining new spatial weighting functions.

Version: 0.1-1
Depends: R (≥ 3.5.0), sf
Imports: Rcpp (≥ 1.0.11)
LinkingTo: Rcpp
Suggests: knitr, xfun, magrittr, glmnet
Published: 2024-09-30
DOI: 10.32614/CRAN.package.pMEM
Author: Guillaume Guénard ORCID iD [aut, cre], Pierre Legendre ORCID iD [ctb]
Maintainer: Guillaume Guénard <guillaume.guenard at umontreal.ca>
License: GPL-3
NeedsCompilation: yes
Citation: pMEM citation info
CRAN checks: pMEM results

Documentation:

Reference manual: pMEM.pdf
Vignettes: Using pMEM for Spatial Modelling with Predictive Moran's Eigenvector Maps (source, R code)

Downloads:

Package source: pMEM_0.1-1.tar.gz
Windows binaries: r-devel: pMEM_0.1-1.zip, r-release: pMEM_0.1-1.zip, r-oldrel: pMEM_0.1-1.zip
macOS binaries: r-release (arm64): pMEM_0.1-1.tgz, r-oldrel (arm64): pMEM_0.1-1.tgz, r-release (x86_64): pMEM_0.1-1.tgz, r-oldrel (x86_64): pMEM_0.1-1.tgz

Linking:

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