Сравнение методов

	Пространственно-временной универсальный крокинг	Пространственно-временной кригинг
Область	Пространственный анализ	Пространственный анализ
Семейство	Regression model	Regression model
Год появления	1999	1999
Автор метода	Kyriakidis & Journel (1999); foundations in Matheron's geostatistics	Cressie & Huang; Kyriakidis & Journel
Тип	Spatiotemporal geostatistical interpolation	Geostatistical interpolation
Основополагающий источник	Kyriakidis, P. C., & Journel, A. G. (1999). Geostatistical space-time models: A review. Mathematical Geology, 31(6), 651-684.	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.
Другие названия	STUK, spatiotemporal universal kriging, space-time kriging with trend, universal kriging in space-time	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time
Связанные	5	4
Сводка	Space-Time Universal Kriging (STUK) is a geostatistical method that interpolates a continuously varying phenomenon across both space and time while explicitly modelling a deterministic trend component. It generalises Universal Kriging to the joint space-time domain, producing unbiased optimal predictions and associated uncertainty estimates at unobserved space-time locations.	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.