63 citations · 178 across the 24 of their papers we have counts for
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stat.ME2017★ 4 cited
The importance of scale in spatially varying coefficient modeling
Daisuke Murakami, Binbin Lu, Paul Harris +4
While spatially varying coefficient (SVC) models have attracted considerable attention in applied science, they have been criticized as being unstable. The objective of this study…
stat.OT2017★ 10 cited
Gaussian spatial regression using the spmoran package: case study examples
Daisuke Murakami
This study demonstrates how to use the "spmoran" package implementing scalable spatial regression models for Gaussian and non-Gaussian data. Implemented models include spatially va…
stat.ME2017★ 63 cited
Eigenvector spatial filtering for large data sets: fixed and random effects approaches
Daisuke Murakami, Daniel A. Griffith
Eigenvector spatial filtering (ESF) is a spatial modeling approach, which has been applied in urban and regional studies, ecological studies, and so on. However, it is computationa…