Package: spmoran
Type: Package
Title: Fast Spatial and Spatio-Temporal Regression using Moran
        Eigenvectors
Version: 0.3.3
Date: 2024-12-05
Authors@R: person(given = "Daisuke",
                    family = "Murakami",
                    role = c("aut", "cre"),
                    email = "dmuraka@ism.ac.jp")
Maintainer: Daisuke Murakami <dmuraka@ism.ac.jp>
Description: 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>).
License: GPL (>= 2)
Encoding: UTF-8
Imports: sf, fields, vegan, Matrix, doParallel, foreach, ggplot2,
        spdep, rARPACK, RColorBrewer, splines, FNN, methods
Suggests: R.rsp, spData (>= 2.3.1)
VignetteBuilder: R.rsp
URL: https://github.com/dmuraka/spmoran
NeedsCompilation: no
Author: Daisuke Murakami [aut, cre]
Repository: CRAN
Packaged: 2024-12-04 16:18:56 UTC; murak
Date/Publication: 2024-12-05 08:30:02 UTC
Built: R 4.4.3; ; 2025-12-29 18:36:20 UTC; windows
