3 citations · 4 across the 5 of their papers we have counts for
6 papers · 1 filter
Resampling simplicial depth
Carsten Jentsch, Stanislav Nagy, Martin Wendler
The simplicial depth (SD) is a commonly used indicator of the centrality of points with respect to distributions on . Asymptotic theory for the…
Projection depth for functional data: Practical issues, computation and applications
Filip Bočinec, Stanislav Nagy, Hyemin Yeon
Statistical analysis of functional data is challenging due to their complex patterns, for which functional depth provides an effective means of reflecting their ordering structure.…
Projection depth for functional data: Theoretical properties
Filip Bočinec, Stanislav Nagy, Hyemin Yeon
We introduce a novel projection depth for data lying in a general Hilbert space, called the regularized projection depth, with a focus on functional data. By regularizing projectio…
Which depth to use to construct functional boxplots?
Stanislav Nagy, Tomáš Mrkvička, Antonio Elías
This paper answers the question of which functional depth to use to construct a boxplot for functional data. It shows that integrated depths, e.g., the popular modified band depth,…
Robust Functional Regression with Discretely Sampled Predictors
Ioannis Kalogridis, Stanislav Nagy
The functional linear model is an important extension of the classical regression model allowing for scalar responses to be modeled as functions of stochastic processes. Yet, despi…
Scalar-on-function local linear regression and beyond
Frédéric Ferraty, Stanislav Nagy
Regressing a scalar response on a random function is nowadays a common situation. In the nonparametric setting, this paper paves the way for making the local linear regression base…