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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "pMEM" in publications use:'
type: software
license: GPL-3.0-only
title: 'pMEM: Predictive Moran''s Eigenvector Maps'
version: 1.0-1
doi: 10.1111/2041-210X.14413
identifiers:
- type: doi
  value: 10.32614/CRAN.package.pMEM
abstract: Calculate Predictive Moran's Eigenvector Maps (pMEM) for spatially-explicit
  prediction of environmental variables, as defined by Guénard and Legendre (2024)
  <https://doi.org/10.1111/2041-210X.14413>. pMEM extends classical MEM by enabling
  interpolation and prediction at unsampled locations using spatial weighting functions
  parameterized by range (and optionally shape). The package implements multiple pMEM
  types (e.g., exponential, Gaussian, linear) and features a modular architecture
  that allows programmers to define custom weighting functions. Designed for ecologists,
  geographers, and spatial analysts working with spatially-structured data.
authors:
- family-names: Guénard
  given-names: Guillaume
  email: guillaume.guenard@gmail.com
  orcid: https://orcid.org/0000-0003-0761-3072
preferred-citation:
  type: article
  title: Spatially-explicit predictions using spatial eigenvector maps.
  authors:
  - family-names: Gu\'enard
    given-names: Guillaume
    email: guillaume.guenard@umontreal.ca
  - family-names: Legendre
    given-names: Pierre
    email: pierre.legendre@umontreal.ca
  journal: Methods in Ecology and Evolution
  year: '2024'
  volume: '15'
  doi: 10.1111/2041-210X.14413
  start: '2129'
  end: '2140'
repository: https://guenardg.r-universe.dev
commit: 4c8baa5f15df5e7823142a8382adc35dfeeb86ec
date-released: '2026-03-06'
contact:
- family-names: Guénard
  given-names: Guillaume
  email: guillaume.guenard@gmail.com
  orcid: https://orcid.org/0000-0003-0761-3072