A Non-Linear Trend Function for Kriging with External Drift Using Least Squares Support Vector Regression
Kanokrat Baisad,
Nawinda Chutsagulprom,
Sompop Moonchai
Abstract:Spatial interpolation of meteorological data can have immense implications on risk management and climate change planning. Kriging with external drift (KED) is a spatial interpolation variant that uses auxiliary information in the estimation of target variables at unobserved locations. However, traditional KED methods with linear trend functions may not be able to capture the complex and non-linear interdependence between target and auxiliary variables, which can lead to an inaccurate estimation. In this work,… Show more
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