Linganisha mbinu

	Kriging ya Nafasi-Wakati	Ukridingi wa Ulimwengu (Ukridingi wenye Mwenendo)
Nyanja	Uchanganuzi wa Kimaeneo	Uchanganuzi wa Kimaeneo
Familia	Regression model	Regression model
Mwaka wa asili	1999	1969
Mwanzilishi	Cressie & Huang; Kyriakidis & Journel	Georges Matheron
Aina	Geostatistical interpolation	Geostatistical interpolation with spatial trend
Chanzo asilia	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.	Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266.
Majina mbadala	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time	kriging with a trend, kriging with drift, trend kriging, evrensel kriging
Zinazohusiana	4	3
Muhtasari	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.	Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances.