Details

Autor(en) / Beteiligte

• FURRER, REINHARD
• GENTON, MARC G.

Titel

Aggregation-cokriging for highly multivariate spatial data

Ist Teil von

• Biometrika, 2011-09, Vol.98 (3), p.615-631

Ort / Verlag

Oxford: Biometrika Trust, University College London

Erscheinungsjahr

2011

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Best linear unbiased prediction of spatially correlated multivariate random processes, often called cokriging in geostatistics, requires the solution of a large linear system based on the covariance and cross-covariance matrix of the observations. For many problems of practical interest, it is impossible to solve the linear system with direct methods. We propose an efficient linear unbiased predictor based on a linear aggregation of the covariables. The primary variable together with this single meta-covariable is used to perform cokriging. We discuss the optimality of the approach under different covariance structures, and use it to create reanalysis type high-resolution historical temperature fields.