Advances in spatial functional statistics

详细信息    查看全文

• 作者：Jorge Mateu ; Elvira Romano
• 关键词：Depth functions ; Functional data ; Functional regression ; Spatial dependence ; Spatial ; depth functional covariates ; Spatial functional data
• 刊名：Stochastic Environmental Research and Risk Assessment
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：31
• 期：1
• 页码：1-6
• 全文大小：353KB
• 刊物类别：Earth and Environmental Science
• 刊物主题：Math. Appl. in Environmental Science; Earth Sciences, general; Probability Theory and Stochastic Processes; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Computa
• 出版者：Springer Berlin Heidelberg
• ISSN：1436-3259
• 卷排序：31

文摘

This is the editorial letter for the special issue dedicated to Spatial Functional Statistics, motivated by the joint VII International Workshop on Spatio-temporal Modelling (METMAVII) and the 2014 meeting of the research group for Statistical Applications to Environmental Problems (GRASPA14), which took place in Turin (Italy) from 10 to 12 September 2014. This special issue summarises and discusses peer-reviewed contributions related to the analysis of functional data showing complex characteristics such as spatial dependence structures. The selection of papers comprises both new methodological proposals and a wide range of applications. In particular, we cover a wide range of statistical aspects, comprising prediction of functional data with spatial dependence, optimal sampling designs using functional covariates, non-parametric clustering methods for dependent functional data, and depth measures for spatially dependent functional data.