.png){kind=icon}
Return
Advances in spatial functional statistics
.png){kind=icon}
OA
AI
DOI：10.1007/s00477-016-1346-z.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Depth functions
Functional data
Functional regression
Spatial dependence
Spatial-depth functional covariates
Spatial functional data
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
3.5K
Citations:
6.9K
Organization
Cited Papers
.png){kind=icon}
ShareSave
ShareSave
View more