63 citations · 178 across the 24 of their papers we have counts for
8 papers · 1 filter
Spatial regression-based transfer learning for prediction problems
Daisuke Murakami, Mami Kajita, Seiji Kajita
Although spatial prediction is widely used for urban and environmental monitoring, its accuracy is often unsatisfactory if only a small number of samples are available in the study…
Transformation-based generalized spatial regression using the spmoran package: Case study examples
Daisuke Murakami
This study presents application examples of generalized spatial regression modeling for count data and continuous non-Gaussian data using the spmoran package (version 0.2.2 onward)…
Spatial prediction of apartment rent using regression-based and machine learning-based approaches with a large dataset
Takahiro Yoshida, Hajime Seya
Employing a large dataset (at most, the order of n = 10^6), this study attempts enhance the literature on the comparison between regression and machine learning (ML)-based rent pri…
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…
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…
Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling
Daisuke Murakami, Yoshiki Yamagata
This study downscales the population and gross domestic product (GDP) scenarios given under Shared Socioeconomic Pathways (SSPs) into 0.5-degree grids. Our downscale approach has t…
A spatiotemporal analysis of participatory sensing data "tweets" and extreme climate events toward real-time urban risk management
Yoshiki Yamagata, Daisuke Murakami, Gareth W. Peters +1
Real-time urban climate monitoring provides useful information that can be utilized to help monitor and adapt to extreme events, including urban heatwaves. Typical approaches to th…