Add to ORKGAbstract We illustrate a depth-based approach in directional statistics, concentrat-ing on a prominent depth function, angular simplicial depth. A new local version of this function is proposed and several depth-based summaries, including angular medians, depth regions and dispersion parameters are considered
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provid...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
Directional data are constrained to lie on the unit sphere of Rq, for some q ≥ 2. To address the lac...
Data depth is a statistical method whose primary aim is to order data of a reference space according...
A non-parametric procedure based on the concept angular depth function is developed for dealing with...
In this thesis we study a special type of multidimentional data - directional data. The main part of...
The notion of the interpoint depth is applied to spherical spaces by us-ing an appropriate angular d...
In this paper, we introduce a new concept of quantiles and depth for directional (circular and spher...
The DD-classifier, which has been extended to the classification of directional objects, is here in...
A procedure is developed in order to deal with the classification problem of objects in circular sta...
We encounter directional data in numerous application areas such as astronomy, biology or engineerin...
Directional data are constrained to lie on the unit sphere of ℝq for some q ≥ 2. To address the lack...
Data depth is a rapidly growing area in nonparametric statistics, especially suited for the analysis...
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provid...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
Directional data are constrained to lie on the unit sphere of Rq, for some q ≥ 2. To address the lac...
Data depth is a statistical method whose primary aim is to order data of a reference space according...
A non-parametric procedure based on the concept angular depth function is developed for dealing with...
In this thesis we study a special type of multidimentional data - directional data. The main part of...
The notion of the interpoint depth is applied to spherical spaces by us-ing an appropriate angular d...
In this paper, we introduce a new concept of quantiles and depth for directional (circular and spher...
The DD-classifier, which has been extended to the classification of directional objects, is here in...
A procedure is developed in order to deal with the classification problem of objects in circular sta...
We encounter directional data in numerous application areas such as astronomy, biology or engineerin...
Directional data are constrained to lie on the unit sphere of ℝq for some q ≥ 2. To address the lack...
Data depth is a rapidly growing area in nonparametric statistics, especially suited for the analysis...
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provid...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
Directional data are constrained to lie on the unit sphere of Rq, for some q ≥ 2. To address the lac...