Cargando…

spind: an R Package to Account for Spatial Autocorrelation in the Analysis of Lattice Data

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....

Descripción completa

Detalles Bibliográficos
Autores principales: Carl, Gudrun, Levin, Sam C, Kühn, Ingolf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pensoft Publishers 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5904461/
https://www.ncbi.nlm.nih.gov/pubmed/29674933
http://dx.doi.org/10.3897/BDJ.6.e20760
Descripción
Sumario: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.