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Локална процена густине језгра×Analiza žarišnih tačaka (Getis-Ord Gi*)×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka1985-19861992
TvoracSilverman, B. W.; Diggle, P. J.Arthur Getis and J. Keith Ord
TipNon-parametric density estimatorLocal spatial statistic
Temeljni izvorSilverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman and Hall, London. ISBN: 978-0412246203Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗
Drugi naziviLocal KDE, adaptive KDE, spatially adaptive kernel density estimation, local density estimationGetis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA
Srodne55
SažetakLocal Kernel Density Estimation (Local KDE) is a non-parametric spatial method that estimates the density of point events at each location by applying a kernel function with a spatially adaptive bandwidth. Unlike global KDE, which uses a fixed bandwidth across the entire study area, Local KDE adjusts the smoothing window according to local data density, capturing fine-scale clustering where events are sparse or concentrated.Hot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation.
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ScholarGateUporedite metode: Local Kernel Density Estimation · Hot Spot Analysis. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare