Indexing and partitioning the spatial linear model for large data sets

We consider four main goals when fitting spatial linear models: 1) estimating covariance parameters, 2) estimating fixed effects, 3) kriging (making point predictions), and 4) block-kriging (predicting the average value over a region). Each of these goals can present different challenges when analyz...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	PloS one 2023-11, Vol.18 (11), p.e0291906-e0291906
Hauptverfasser:	Ver Hoef, Jay M, Dumelle, Michael, Higham, Matt, Peterson, Erin E, Isaak, Daniel J
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Basis functions Computer and Information Sciences Confidence intervals Covariance matrix Datasets Earth Sciences Engineering and Technology Estimates Evaluation Geospatial data Geostatistics Indexing Linear models (Statistics) Linear regression models Nearest-neighbor Parameter estimation Partial differential equations Partitions (mathematics) Physical Sciences Predictions Random variables Regression analysis Research and Analysis Methods Simulation methods Spatial data Tapering Topology Variance analysis
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!