Package: pMEM 0.1-1

Guillaume Guénard

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.

Authors:Guillaume Guénard [aut, cre], Pierre Legendre [ctb]

pMEM_0.1-1.tar.gz
pMEM_0.1-1.tar.gz(r-4.5-noble)pMEM_0.1-1.tar.gz(r-4.4-noble)
pMEM_0.1-1.tgz(r-4.4-emscripten)pMEM_0.1-1.tgz(r-4.3-emscripten)
pMEM.pdf |pMEM.html✨
pMEM/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • geoMite - Borcard's Oribatid Mite Data Set - Geographic Information System Version -
  • salmon - The St. Marguerite River Altantic Salmon Parr Transect

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

2.00 score 7 scripts 125 downloads 4 exports 13 dependencies

Last updated 3 months agofrom:bdc021c074. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 18 2024
R-4.5-linux-x86_64OKDec 18 2024

Exports:genDistMetricgenDWFgenSEFgetMinMSE

Dependencies:classclassIntDBIe1071KernSmoothmagrittrMASSproxyRcpps2sfunitswk

Using pMEM for Spatial Modelling with Predictive Moran's Eigenvector Maps

Guillaume Guénard, Pierre Legendre

Rendered fromUsing_pMEM.Rmdusingknitr::rmarkdownon Dec 18 2024.

Last update: 2024-10-01
Started: 2024-10-01