Σύγκριση μεθόδων

	Συν-κριγκινγκ: Πολυμεταβλητή Γεωστατιστική Παρεμβολή	Παλινδρόμηση Πολλαπλής Κλίμακας με Γεωγραφική Στάθμιση (MGWR)
Πεδίο	Χωρική Ανάλυση	Χωρική Ανάλυση
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1965-1978	2017
Δημιουργός	Matheron, G.; extended by Journel & Huijbregts	A. Stewart Fotheringham, Wei Yang, and Wei Kang
Τύπος	Geostatistical interpolation	Local spatial regression
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	cokriging, co-regionalization kriging, multivariate kriging, CK	MGWR, multiscale GWR, multi-scale geographically weighted regression, variable-bandwidth GWR
Συναφείς	5	5
Σύνοψη	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.