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Panel Network-Based Spatial Analysis×Prostorna autokorelacija×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka2000s–2010s1950
TvoracDeveloped from LeSage & Pace spatial econometrics and Elhorst panel spatial frameworksP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TipPanel spatial regressionSpatial statistic / exploratory spatial data analysis
Temeljni izvorLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
Drugi nazivipanel spatial network analysis, longitudinal network spatial analysis, panel network spatial econometrics, PNBSAspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Srodne55
SažetakPanel Network-Based Spatial Analysis extends standard spatial econometric models to repeated-measures (panel) data by representing spatial dependence through network connectivity rather than simple geographic proximity. It captures how units connected in a network influence each other's outcomes over time, while controlling for unit-level and time-level fixed effects.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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ScholarGateUporedite metode: Panel Network-Based Spatial Analysis · Spatial Autocorrelation. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare