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spmoran (version 0.1.7)
Moran Eigenvector-Based Spatial Regression Models
Description
Functions for estimating Moran's eigenvector-based spatial regression models. For details see Murakami (2019)
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Install
install.packages('spmoran')
Monthly Downloads
402
Version
0.1.7
License
GPL (>= 2)
Maintainer
Daisuke Murakami
Last Published
July 23rd, 2019
Functions in spmoran (0.1.7)
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meigen0
Nystrom extension of Moran's eigenvectors
plot_qr
Plot quantile regression coefficients estimated from SF-UQR
lslm
Low rank spatial lag model (LSLM) estimation
esf
Spatial regression with eigenvector spatial filtering
besf
Memory-free implementation of the RE-ESF model for very large datasets
lsem
Low rank spatial error model (LSEM) estimation
meigen
Extraction of Moran's eigenvectors
meigen_f
Fast approximation of Moran's eigenvectors
predict0
Spatial prediction using eigenvector spatial filtering (ESF) or random effects ESF
besf_vc
Spatially varying coefficient modeling for very large datasets
weigen
Extraction of eigenvectors from a spatial weight matrix
resf_vc
Spatially varying coefficient modeling with/without automatic coefficient selection
resf_qr
Spatial filter unconditional quantile regression
predict0_vc
Prediction of explained variables and spatially varying coefficients
resf
Spatial regression with random effects eigenvector spatial filtering