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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Krigagem Ordinária de Painel×Autocorrelação Espacial×
ÁreaAnálise espacialAnálise espacial
FamíliaRegression modelRegression model
Ano de origem1963 (Ordinary Kriging origin); panel extensions formalized in 1990s–2000s1950
Autor originalExtension 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)
TipoGeostatistical spatial interpolationSpatial statistic / exploratory spatial data analysis
Fonte seminalCressie, 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 ↗
Outros nomesordinary kriging for panel data, longitudinal ordinary kriging, repeated-measures spatial kriging, panel geostatistical interpolationspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Relacionados65
ResumoPanel 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.
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ScholarGateComparar métodos: Panel Ordinary Kriging · Spatial Autocorrelation. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare