CRAN/E | spmoran

spmoran

Fast Spatial Regression using Moran Eigenvectors

Installation

About

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) .

Key Metrics

Version 0.2.3
Published 2024-01-23 100 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks spmoran results

Downloads

Yesterday 65 +442%
Last 7 days 209 +32%
Last 30 days 607 -4%
Last 90 days 1.857 -7%
Last 365 days 7.852 -12%

Maintainer

Maintainer

Daisuke Murakami

dmuraka@ism.ac.jp

Authors

Daisuke Murakami

Material

Reference manual
Package source

In Views

Spatial

Vignettes

Spatial regression using the spmoran package: Boston housing price data examples
Transformation-based generalized spatial regression using the spmoran package: Case study examples

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

spmoran archive

Imports

sf
fields
vegan
Matrix
doParallel
foreach
ggplot2
spdep
rARPACK
RColorBrewer
splines
FNN
methods

Suggests

R.rsp