Methoden vergleichen

	Co-Kriging: Multivariate Geostatistische Interpolation	Geographisch gewichtete Regression (GWR)
Fachgebiet	Räumliche Analyse	Räumliche Analyse
Familie	Regression model	Regression model
Entstehungsjahr	1965-1978	2002
Urheber	Matheron, G.; extended by Journel & Huijbregts	Fotheringham, Brunsdon & Charlton
Typ	Geostatistical interpolation	Local spatial regression
Wegweisende Quelle	Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Aliasnamen	cokriging, co-regionalization kriging, multivariate kriging, CK	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Verwandt	5	5
Zusammenfassung	Co-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.