手法を比較

	時空間的空間回帰分析	空間時間クリギング
分野	空間分析	空間分析
系統	Regression model	Regression model
提唱年	1990s–2000s	1999
提唱者	Anselin, LeSage, Pace and colleagues in spatial econometrics	Cressie & Huang; Kyriakidis & Journel
種類	Spatio-temporal regression model	Geostatistical interpolation
原典	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.
別名	spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time
関連	6	4
概要	Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data.	Space-Time Kriging is a geostatistical interpolation method that predicts an unknown variable at any location and time by borrowing strength from nearby observations in both space and time simultaneously. It models the joint spatial-temporal covariance structure through a space-time variogram, then uses optimal linear weights to produce predictions with quantified uncertainty.