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क्षेत्रस्थानिक विश्लेषणस्थानिक विश्लेषण
परिवारRegression modelRegression model
उद्भव वर्ष19991969
प्रवर्तकCressie & Huang; Kyriakidis & JournelGeorges Matheron
प्रकारGeostatistical interpolationGeostatistical interpolation with spatial trend
मौलिक स्रोतCressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340. DOI ↗Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗
उपनामspatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-timekriging with a trend, kriging with drift, trend kriging, evrensel kriging
संबंधित43
सारांशSpace-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.
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