Compara mètodes

	Co-kriging: Interpolació Geostadística Multivariant	Regressió Geogràficament Ponderada Multiescala (MGWR)
Camp	Anàlisi espacial	Anàlisi espacial
Família	Regression model	Regression model
Any d'origen	1965-1978	2017
Autor original	Matheron, G.; extended by Journel & Huijbregts	A. Stewart Fotheringham, Wei Yang, and Wei Kang
Tipus	Geostatistical interpolation	Local spatial regression
Font seminal	Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561	Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265.
Àlies	cokriging, co-regionalization kriging, multivariate kriging, CK	MGWR, multiscale GWR, multi-scale geographically weighted regression, variable-bandwidth GWR
Relacionats	5	5
Resum	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.	Multiscale Geographically Weighted Regression (MGWR) is a local spatial regression framework that relaxes the single-bandwidth constraint of standard GWR by allowing each predictor to operate at its own spatial scale. Each coefficient surface is calibrated with its own bandwidth, enabling the model to distinguish drivers that vary slowly across space from those that vary sharply.