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क्षेत्रस्थानिक विश्लेषणस्थानिक विश्लेषण
परिवारRegression modelRegression model
उद्भव वर्ष1993–19981969
प्रवर्तकDiggle, Tawn & Moyeed; Handcock & SteinGeorges Matheron
प्रकारBayesian spatial interpolationGeostatistical interpolation with spatial trend
मौलिक स्रोतDiggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(3), 299–350. DOI ↗Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗
उपनामBayesian geostatistics, model-based geostatistics, Bayesian spatial interpolation, stochastic krigingkriging with a trend, kriging with drift, trend kriging, evrensel kriging
संबंधित53
सारांशBayesian Kriging embeds classical geostatistical interpolation inside a full probabilistic framework. Instead of treating variogram parameters as fixed point estimates, it places prior distributions on them and updates these priors with observed spatial data to obtain a posterior distribution. Predictions at unsampled locations are then marginalised over this uncertainty, yielding honest predictive intervals that account for both spatial dependence and parameter 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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ScholarGateविधियों की तुलना करें: Bayesian Kriging · Universal Kriging. 2026-06-17 को यहाँ से प्राप्त https://scholargate.app/hi/compare