A Fay-Herriot Type Approach for Better Prediction in Multi-indexed Response with Application to Arctic Seawater Data Analysis

摘要

We consider the problem of fitting a nonparametric curve to Arctic Ocean temperature data. Since several alternative curves may be fitted, we consider borrowing strength over fitted curves to create an esemble fit. This lead to a novel exercise involving nonparametric curve fitting and small area methods. Our results indicate that climate data analysis is a complex process, and standard statistical techniques may need to be considerably enhanced for applicability to big data arising from climate studies.