63 citations · 178 across the 24 of their papers we have counts for
5 papers · 1 filter
Spatially Clustered Regression
Shonosuke Sugasawa, Daisuke Murakami
Spatial regression or geographically weighted regression models have been widely adopted to capture the effects of auxiliary information on a response variable of interest over a r…
Scalable model selection for spatial additive mixed modeling: application to crime analysis
Daisuke Murakami, Mami Kajita, Seiji Kajita
A rapid growth in spatial open datasets has led to a huge demand for regression approaches accommodating spatial and non-spatial effects in big data. Regression model selection is…
Balancing spatial and non-spatial variation in varying coefficient modeling: a remedy for spurious correlation
Daisuke Murakami, Daniel A. Griffith
This study discusses the importance of balancing spatial and non-spatial variation in spatial regression modeling. Unlike spatially varying coefficients (SVC) modeling, which is po…
The GWR route map: a guide to the informed application of Geographically Weighted Regression
Alexis Comber, Chris Brunsdon, Martin Charlton +8
Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of social and environmental data. It allows spatial heterogeneities in processes and relationships…
Spatiotemporal analysis of urban heatwaves using Tukey g-and-h random field models
Daisuke Murakami, Gareth W. Peters, Tomoko Matsui +1
The statistical quantification of temperature processes for the analysis of urban heat island (UHI) effects and local heat-waves is an increasingly important application domain in…