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קריגינג גלובלי×אוטוקורלציה מרחבית×
תחוםניתוח מרחביניתוח מרחבי
משפחהRegression modelRegression model
שנת המקור1960s–19931950
הוגה השיטהGeorges 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)
סוגGeostatistical interpolationSpatial statistic / exploratory spatial data analysis
מקור מכונןCressie, 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 ↗
כינוייםglobal-neighborhood kriging, full-data kriging, exhaustive kriging, non-local krigingspatial dependence, geographic autocorrelation, spatial clustering measure, SA
קשורות55
תקצירGlobal 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.
ScholarGateמערך נתונים
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  1. v1
  2. 2 מקורות
  3. PUBLISHED

מעבר לחיפוש הורדת מצגת

ScholarGateהשוואת שיטות: Global Kriging · Spatial Autocorrelation. אוחזר בתאריך 2026-06-18 מתוך https://scholargate.app/he/compare