In this paper we introduce a depth measure for geostatistical functional data. The aim is to provide a tool which allows to get a center-outward ordering of functional data recorded by sensors placed on a geographic area. Although the topic of ordering functional data has already been addressed in the literature, no proposal analyzes the case in which there is a spatial dependence among the curves as a result of the spatial location. With this aim, we extend a well known depth measure for functional data by introducing a new component in the measurement, which accounts for the spatial covariance. Through an application of the proposed method to a wide range of simulated cases, we will show its effectiveness in discovering an useful...
We propose robust inference tools for functional data based on the notion of depth for curves. We ex...
Classification problems of functional data arise naturally in many applications. Several approaches...
Abstract We illustrate a depth-based approach in directional statistics, concentrat-ing on a promine...
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provid...
In this paper, we address the problem of getting order statistics for georeferenced functional data ...
Application of depth methods to functional data provides new tools of analysis, in particular an\ud ...
A new definition of depth for functional observations is introduced based on the notion of "half-reg...
In this paper we propose an outlier detection method for geostatistical functional data. Our approa...
A new definition of depth for functional observations is introduced based on the notion of “half-reg...
Functional data are becoming increasingly available and tractable because of the last technological...
Abstract: Functional Data Analysis is a relatively new branch in Statis-tics. Experiments where a co...
The statistical analysis of functional data is a growing need in many research areas. We propose a n...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
Functional Data Analysis is a relatively new branch in Statistics. Experiments where a complete func...
A recent and highly attractive area of research in statistics is the analysis of functional data. In...
We propose robust inference tools for functional data based on the notion of depth for curves. We ex...
Classification problems of functional data arise naturally in many applications. Several approaches...
Abstract We illustrate a depth-based approach in directional statistics, concentrat-ing on a promine...
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provid...
In this paper, we address the problem of getting order statistics for georeferenced functional data ...
Application of depth methods to functional data provides new tools of analysis, in particular an\ud ...
A new definition of depth for functional observations is introduced based on the notion of "half-reg...
In this paper we propose an outlier detection method for geostatistical functional data. Our approa...
A new definition of depth for functional observations is introduced based on the notion of “half-reg...
Functional data are becoming increasingly available and tractable because of the last technological...
Abstract: Functional Data Analysis is a relatively new branch in Statis-tics. Experiments where a co...
The statistical analysis of functional data is a growing need in many research areas. We propose a n...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
Functional Data Analysis is a relatively new branch in Statistics. Experiments where a complete func...
A recent and highly attractive area of research in statistics is the analysis of functional data. In...
We propose robust inference tools for functional data based on the notion of depth for curves. We ex...
Classification problems of functional data arise naturally in many applications. Several approaches...
Abstract We illustrate a depth-based approach in directional statistics, concentrat-ing on a promine...