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التوزيع العادي اللوحي (Panel Ordinary Kriging)×تحليل الانحدار المكاني للبيانات المقطعية (Panel Spatial Regression)×
المجالالتحليل المكانيالتحليل المكاني
العائلةRegression modelRegression model
سنة النشأة1963 (Ordinary Kriging origin); panel extensions formalized in 1990s–2000s1988-2014
صاحب الطريقةExtension of Ordinary Kriging (Matheron, 1963) to panel/longitudinal spatial settingsAnselin, Elhorst, and colleagues in spatial econometrics
النوعGeostatistical spatial interpolationSpatial panel regression
المصدر التأسيسيCressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience. ISBN: 978-0471002550Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408
الأسماء البديلةordinary kriging for panel data, longitudinal ordinary kriging, repeated-measures spatial kriging, panel geostatistical interpolationspatial panel model, panel spatial econometrics, spatial panel data regression, PSR
ذات صلة66
الملخصPanel Ordinary Kriging extends the classical geostatistical interpolation method — Ordinary Kriging — to panel (longitudinal) datasets where the same set of spatial locations is observed repeatedly over multiple time periods. It produces optimal linear unbiased predictions at unsampled locations for each time slice, accounting for spatial dependence while leveraging the temporal structure of the repeated observations.Panel Spatial Regression extends standard panel data models by explicitly accounting for spatial dependence among cross-sectional units observed over time. It combines the temporal control of panel fixed or random effects with a spatial weights matrix that encodes geographic or network proximity, yielding unbiased and efficient estimates when observations are spatially correlated across units.
ScholarGateمجموعة البيانات
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  2. 2 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Panel Ordinary Kriging · Panel Spatial Regression. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare