Functions for estimating spatial varying coefficient models, mixed models, and other spatial regression models for Gaussian and non-Gaussian data. Moran eigenvectors are used to an approximate Gaussian process modeling which is interpretable in terms of the Moran coefficient. The GP is used for modeling the spatial processes in residuals and regression coefficients. For details see Murakami (2021) <arXiv:1703.04467>.
| Version: | 0.2.2.6 |
| Imports: | sp, fields, vegan, Matrix, doParallel, foreach, ggplot2, spdep, rARPACK, RColorBrewer, splines, FNN, methods |
| Suggests: | R.rsp, rgdal |
| Published: | 2022-09-05 |
| Author: | Daisuke Murakami |
| Maintainer: | Daisuke Murakami <dmuraka at ism.ac.jp> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| In views: | Spatial |
| CRAN checks: | spmoran results |
| Package source: | spmoran_0.2.2.6.tar.gz |
| Windows binaries: | r-devel: spmoran_0.2.2.6.zip, r-release: spmoran_0.2.2.6.zip, r-oldrel: spmoran_0.2.2.6.zip |
| macOS binaries: | r-release (arm64): spmoran_0.2.2.5.tgz, r-oldrel (arm64): spmoran_0.2.2.5.tgz, r-release (x86_64): spmoran_0.2.2.6.tgz, r-oldrel (x86_64): spmoran_0.2.2.6.tgz |
| Old sources: | spmoran archive |
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