363 citations · 772 across the 19 of their papers we have counts for
13 papers · 1 filter
Inference for sparsely sampled Gauss-Markov processes under outcome-dependent dropout
Alexander Aue, Siegfried Hörmann, Maximilian Ofner
We consider sparsely observed functional data generated by a latent Gauss-Markov process modeled through a linear stochastic differential equation (SDE). Motivated by an applicatio…
Quantifying and testing dependence to categorical variables
Siegfried Hörmann, Daniel Strenger-Galvis
We suggest a dependence coefficient between a categorical variable and some general variable taking values in a metric space. We derive important theoretical properties and study t…
Azadkia-Chatterjee's dependence coefficient for infinite dimensional data
Siegfried Hörmann, Daniel Strenger
We extend the scope of Azadkia-Chatterjee's dependence coefficient between a scalar response and a multivariate covariate to the case where takes values in a general me…
Covariate-informed reconstruction of partially observed functional data via factor models
Maximilian Ofner, Siegfried Hörmann
This paper studies linear reconstruction of partially observed functional data which are recorded on a discrete grid. We propose a novel estimation approach based on approximate fa…
Estimating the conditional distribution in functional regression problems
Siegfried Hörmann, Thomas Kuenzer, Gregory Rice
We consider the problem of consistently estimating the conditional distribution of a functional data object given covariates in a general…
Consistently recovering the signal from noisy functional data
Siegfried Hörmann, Fatima Jammoul
In practice most functional data cannot be recorded on a continuum, but rather at discrete time points. It is also quite common that these measurements come with an additive error,…