In this thesis we study a special type of multidimentional data - directional data. The main part of this thesis consists of defining and comparing different ways of order- ing directional data. The most important functions used for ordering directional data presented in this thesis are angular depths. We will describe importnant properties of angular depths and we will discuss wheter each angular depth satisfies the formulated desirable properties. Using previously defined angular depths and median we show two ways of drawing the circular version of a boxplot.
This paper sheds some new light on the multivariate (projectional) quantiles recently introduced in ...
Directional data are constrained to lie on the unit sphere of ℝq for some q ≥ 2. To address the lack...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
In this paper, we introduce a new concept of quantiles and depth for directional (circular and spher...
Abstract We illustrate a depth-based approach in directional statistics, concentrat-ing on a promine...
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...
We encounter directional data in numerous application areas such as astronomy, biology or engineerin...
Title: Graphical methods for directional data Author: Anastasia Tyuleneva Department: Department of ...
We introduce classifiers based on directional quantiles. We derive theoretical results for selecting...
A procedure is developed in order to deal with the classification problem of objects in circular sta...
The notion of the interpoint depth is applied to spherical spaces by us-ing an appropriate angular d...
summary:Although many words have been written about two recent directional (regression) quantile con...
This paper proposes various nonparametric tools for directional data based on measure transportation...
AbstractA new projection-based definition of quantiles in a multivariate setting is proposed. This a...
This paper sheds some new light on the multivariate (projectional) quantiles recently introduced in ...
Directional data are constrained to lie on the unit sphere of ℝq for some q ≥ 2. To address the lack...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...
In this paper, we introduce a new concept of quantiles and depth for directional (circular and spher...
Abstract We illustrate a depth-based approach in directional statistics, concentrat-ing on a promine...
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...
We encounter directional data in numerous application areas such as astronomy, biology or engineerin...
Title: Graphical methods for directional data Author: Anastasia Tyuleneva Department: Department of ...
We introduce classifiers based on directional quantiles. We derive theoretical results for selecting...
A procedure is developed in order to deal with the classification problem of objects in circular sta...
The notion of the interpoint depth is applied to spherical spaces by us-ing an appropriate angular d...
summary:Although many words have been written about two recent directional (regression) quantile con...
This paper proposes various nonparametric tools for directional data based on measure transportation...
AbstractA new projection-based definition of quantiles in a multivariate setting is proposed. This a...
This paper sheds some new light on the multivariate (projectional) quantiles recently introduced in ...
Directional data are constrained to lie on the unit sphere of ℝq for some q ≥ 2. To address the lack...
In this thesis the theory of depth functions is researched. Depth functions are functions that measu...