A universal kriging approach for spatial functional data

作者：Caballero William; Giraldo Ramon^*; Mateu Jorge

来源：Stochastic Environmental Research and Risk Assessment, 2013, 27(7): 1553-1563.

DOI：10.1007/s00477-013-0691-4

• Cross-validation
• Functional random variable
• Smoothed curves
• Trace-variogram
• Universal kriging

In a wide range of scientific fields the outputs coming from certain measurements often come in form of curves. In this paper we give a solution to the problem of spatial prediction of non-stationary functional data. We propose a new predictor by extending the classical universal kriging predictor for univariate data to the context of functional data. Using an approach similar to that used in univariate geostatistics we obtain a matrix system for estimating the weights of each functional variable on the prediction. The proposed methodology is validated by analyzing a real dataset corresponding to temperature curves obtained in several weather stations of Canada.

• 出版日期2013-10