pMEM: Predictive Moran's Eigenvector Maps
Calculate Predictive Moran's Eigenvector Maps (pMEM) for
spatially-explicit prediction of environmental variables, as defined by
Guénard and Legendre (2024) <doi: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.
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