Cross validation of kriging in a unique neighborhood |
| |
Authors: | Olivier Dubrule |
| |
Institution: | 1. Fluor Mining & Metals, Inc., 10 Twin Dolphin Drive, 94065, Redwood City, California, USA
|
| |
Abstract: | Cross validation is an appropriate tool for testing interpolation methods: it consists of leaving out one data point at a time, and determining how well this point can be estimated from the other data. Cross validation is often used for testing “moving neighborhood” kriging models; in this case, each unknown value is predicted from a small number of surrounding data. In “unique neighborhood” kriging algorithms, each estimation uses all the available data; as a result, cross validation would spend much computer time. For instance, with ndata points it would cost at least the resolution of nsystems of n × nlinear equations (each with a different matrix).Here, we present a much faster method for cross validation in a unique neighborhood. Instead of solving nsystems n × n,it only requires the inversion of one n × nmatrix. We also generalized this method to leaving out several points instead of one. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|