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spmoran
View on CRAN: Click
here
Download and install spmoran package within the R console
Install from CRAN:
install.packages("spmoran")
Install from Github:
library("remotes")
install_github("cran/spmoran")
Install by package version:
library("remotes")
install_version("spmoran", "0.3.3")
Attach the package and use:
library("spmoran")
Maintained by
Daisuke Murakami
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.spmoran . https://github.com/dmuraka/spmoran . spmoran results . spmoran.pdf . Spatial regression using the spmoran package: Boston housing price data examples . Spatio-temporally varying coefficient modeling using the spmoran package . Transformation-based generalized spatial regression using the spmoran package: Case study examples . spmoran_0.3.3.tar.gz . spmoran_0.3.3.zip . spmoran_0.3.3.zip . spmoran_0.3.3.zip . spmoran_0.3.3.tgz . spmoran_0.3.3.tgz . spmoran_0.3.3.tgz . spmoran_0.3.3.tgz . spmoran_0.3.3.tgz . spmoran_0.3.3.tgz . spmoran archive . https://CRAN.R-project.org/package=spmoran .
First Published: 2017-03-12
Latest Update: 2023-04-28
Description:
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 spatial Gaussian processes. These processes are used for modeling the spatial processes in residuals and regression coefficients. For details see Murakami (2021) <doi:10.48550/arXiv.1703.04467>.
How to cite:
Daisuke Murakami (2017). spmoran: Fast Spatial and Spatio-Temporal Regression using Moran Eigenvectors. R package version 0.3.3, https://cran.r-project.org/web/packages/spmoran. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.0 (2017-03-12 18:43), 0.1.1 (2017-06-23 15:21), 0.1.2 (2017-09-15 17:17), 0.1.3 (2018-04-10 06:46), 0.1.4 (2018-05-02 14:32), 0.1.5 (2018-08-09 17:10), 0.1.6.1 (2019-01-23 10:10), 0.1.6.2 (2019-02-25 19:20), 0.1.6 (2018-10-06 07:20), 0.1.7.1 (2019-07-24 23:30), 0.1.7.2 (2019-12-11 15:20), 0.1.7 (2019-07-24 00:30), 0.2.0-1 (2020-05-31 16:30), 0.2.0-2 (2020-08-03 06:30), 0.2.0 (2020-05-20 16:20), 0.2.1 (2021-01-11 00:30), 0.2.2.1 (2021-11-18 10:10), 0.2.2.2 (2022-01-03 19:00), 0.2.2.3 (2022-04-27 19:30), 0.2.2.4 (2022-06-28 04:40), 0.2.2.5 (2022-08-08 09:30), 0.2.2.6 (2022-09-05 08:00), 0.2.2.7 (2023-04-12 14:10), 0.2.2.8 (2023-04-23 18:20), 0.2.2.9 (2023-04-28 23:10), 0.2.2 (2021-09-13 10:40), 0.2.3 (2024-01-23 18:40), 0.3.0 (2024-09-25 00:30), 0.3.1 (2024-10-13 01:40), 0.3.2 (2024-12-03 18:10)
Other packages that cited spmoran R package
View spmoran citation profile
Other R packages that spmoran depends,
imports, suggests or enhances
Complete documentation for spmoran
Functions, R codes and Examples using
the spmoran R package
Some associated functions: addlearn_local . besf . besf_vc . coef_marginal . coef_marginal_vc . esf . lsem . lslm . meigen . meigen0 . meigen_f . nongauss_y . plot_n . plot_qr . plot_s . predict0 . predict0_vc . resf . resf_qr . resf_vc . weigen .
Some associated R codes: addlearn_local.R . besf.R . besf_vc.R . coef_marginal.R . coef_marginal_vc.R . esf.R . lsem.R . lslm.R . meigen.R . meigen0.R . meigen_f.R . nongauss_y.R . plot_n.R . plot_qr.R . plot_s.R . predict0.R . predict0_vc.R . resf.R . resf_qr.R . resf_vc.R . weigen.R . Full spmoran package functions and examples
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