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spind: an R Package to Account for Spatial Autocorrelation in the Analysis of Lattice Data.
Carl, Gudrun; Levin, Sam C; Kühn, Ingolf.
Afiliación
  • Carl G; Helmholtz Centre for Environmental Research - UFZ, Halle (Saale), Germany.
  • Levin SC; Martin Luther Universität Halle-Wittenberg, Halle (Saale), Germany.
  • Kühn I; German Centre for Integrative Biodiversity (iDiv), Leipzig, Germany.
Biodivers Data J ; (6): e20760, 2018.
Article en En | MEDLINE | ID: mdl-29674933
ABSTRACT
spind is an R package aiming to provide a useful toolkit to account for spatial dependence in the analysis of lattice data. Grid-based data sets in spatial modelling often exhibit spatial dependence, i.e. values sampled at nearby locations are more similar than those sampled further apart. spind methods, described here, take this kind of two-dimensional dependence into account and are sensitive to its variation across different spatial scales. Methods presented to account for spatial autocorrelation are based on the two fundamentally different approaches of generalised estimating equations as well as wavelet-revised methods. Both methods are extensions to generalised linear models. spind also provides functions for multi-model inference and scaling by wavelet multiresolution regression. Since model evaluation is essential for assessing prediction accuracy in species distribution modelling, spind additionally supplies users with spatial accuracy measures, i.e. measures that are sensitive to the spatial arrangement of the predictions.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Biodivers Data J Año: 2018 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Biodivers Data J Año: 2018 Tipo del documento: Article País de afiliación: Alemania