A collection of functions for estimating spatial and spatio-temporal regression models. Moran eigenvectors are used as spatial basis functions to efficiently approximate spatially dependent Gaussian processes (i.e., random effects eigenvector spatial filtering; see Murakami and Griffith 2015 <doi:10.1007/s10109-015-0213-7>). The implemented models include linear regression with residual spatial dependence, spatially/spatio-temporally varying coefficient models (Murakami et al., 2017, 2024; <doi:10.1016/j.spasta.2016.12.001>,<doi:10.48550/arXiv.2410.07229>), spatially filtered unconditional quantile regression (Murakami and Seya, 2019 <doi:10.1002/env.2556>), Gaussian and non-Gaussian spatial mixed models through compositionally-warping (Murakami et al. 2021, <doi:10.1016/j.spasta.2021.100520>).
Version: | 0.3.1 |
Imports: | sf, fields, vegan, Matrix, doParallel, foreach, ggplot2, spdep, rARPACK, RColorBrewer, splines, FNN, methods |
Suggests: | R.rsp |
Published: | 2024-10-12 |
DOI: | 10.32614/CRAN.package.spmoran |
Author: | Daisuke Murakami [aut, cre] |
Maintainer: | Daisuke Murakami <dmuraka at ism.ac.jp> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/dmuraka/spmoran |
NeedsCompilation: | no |
In views: | Spatial |
CRAN checks: | spmoran results |
Package source: | spmoran_0.3.1.tar.gz |
Windows binaries: | r-devel: spmoran_0.3.1.zip, r-release: spmoran_0.3.1.zip, r-oldrel: spmoran_0.3.1.zip |
macOS binaries: | r-release (arm64): spmoran_0.3.1.tgz, r-oldrel (arm64): spmoran_0.3.1.tgz, r-release (x86_64): spmoran_0.3.1.tgz, r-oldrel (x86_64): spmoran_0.3.1.tgz |
Old sources: | spmoran archive |
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