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cff-version: 1.2.0
message: 'To cite package "spmoran" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'spmoran: Fast Spatial and Spatio-Temporal Regression using Moran Eigenvectors'
version: 0.3.3
doi: 10.32614/CRAN.package.spmoran
abstract: 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 <https://doi.org/ 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;
  <https://doi.org/10.1016/j.spasta.2016.12.001>,<https://doi.org/10.48550/arXiv.2410.07229>),
  spatially filtered unconditional quantile regression (Murakami and Seya, 2019 <https://doi.org/10.1002/env.2556>),
  Gaussian and non-Gaussian spatial mixed models through compositionally-warping (Murakami
  et al. 2021, <https://doi.org/10.1016/j.spasta.2021.100520>).
authors:
- family-names: Murakami
  given-names: Daisuke
  email: dmuraka@ism.ac.jp
repository: https://CRAN.R-project.org/package=spmoran
repository-code: https://github.com/dmuraka/spmoran
url: https://github.com/dmuraka/spmoran
date-released: '2024-12-05'
contact:
- family-names: Murakami
  given-names: Daisuke
  email: dmuraka@ism.ac.jp