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Co-kriging: Uingizaji wa Njia Mbalimbali za Kijiografia×Usuli wa Kawaida wa Kijiografia (GWR)×
NyanjaUchanganuzi wa KimaeneoUchanganuzi wa Kimaeneo
FamiliaRegression modelRegression model
Mwaka wa asili1965-19782002
MwanzilishiMatheron, G.; extended by Journel & HuijbregtsFotheringham, Brunsdon & Charlton
AinaGeostatistical interpolationLocal spatial regression
Chanzo asiliaJournel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Majina mbadalacokriging, co-regionalization kriging, multivariate kriging, CKGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Zinazohusiana55
MuhtasariCo-kriging is a geostatistical interpolation technique that predicts the spatial distribution of a primary variable by leveraging its spatial cross-correlation with one or more secondary (co-) variables. It extends ordinary kriging to multivariate settings, yielding more accurate predictions when the secondary variable is more densely sampled or spatially correlated with the primary variable of interest.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
ScholarGateSeti ya data
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  1. v1
  2. 1 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Co-kriging · Geographically Weighted Regression. Imepatikana 2026-06-19 kutoka https://scholargate.app/sw/compare