15 citations · 17 across the 5 of their papers we have counts for
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stat.AP2022
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…
stat.AP2020★ 1 cited
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…
stat.AP2017★ 15 cited
Crime Prediction by Data-Driven Green's Function method
Mami Kajita, Seiji Kajita
We develop an algorithm that forecasts cascading events, by employing a Green's function scheme on the basis of the self-exciting point process model. This method is applied to ope…