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Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Globální kriging×Prostorová autokorelace×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku1960s–19931950
TvůrceGeorges Matheron (kriging framework); global neighborhood usage formalized in applied geostatisticsP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TypGeostatistical interpolationSpatial statistic / exploratory spatial data analysis
Původní zdrojCressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience. ISBN: 978-0471002550Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
Další názvyglobal-neighborhood kriging, full-data kriging, exhaustive kriging, non-local krigingspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Příbuzné55
ShrnutíGlobal Kriging is the ordinary kriging interpolation procedure applied using all available sample points as the neighborhood — no spatial search window limits which data contribute to each prediction. It produces optimal linear unbiased predictions of an unobserved value at any target location, with associated prediction-error variances, by exploiting a fitted variogram model that encodes spatial autocorrelation across the entire dataset.Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.
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ScholarGatePorovnat metody: Global Kriging · Spatial Autocorrelation. Získáno 2026-06-18 z https://scholargate.app/cs/compare