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Панелен обикновен кригинг×Пространствена автокорелация×
ОбластПространствен анализПространствен анализ
СемействоRegression modelRegression model
Година на възникване1963 (Ordinary Kriging origin); panel extensions formalized in 1990s–2000s1950
СъздателExtension of Ordinary Kriging (Matheron, 1963) to panel/longitudinal spatial settingsP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
ТипGeostatistical spatial interpolationSpatial statistic / exploratory spatial data analysis
Основополагащ източникCressie, 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 ↗
Други названияordinary kriging for panel data, longitudinal ordinary kriging, repeated-measures spatial kriging, panel geostatistical interpolationspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Свързани65
РезюмеPanel 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.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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Panel Ordinary Kriging · Spatial Autocorrelation. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare