activity
20182026
most citedWhittle estimation for stationary state space models with finite second moments

2 citations · 2 across the 5 of their papers we have counts for

collaborators

9 papers

math.ST2026

Statistical inference for extremal directions in high-dimensional spaces

Lucas Butsch, Vicky Fasen-Hartmann

In multivariate extreme value statistics, the first step in understanding the dependence structure of extremes is identifying the directions in which they occur. The novelty of thi…

stat.ME2025

Estimation of the number of principal components in high-dimensional multivariate extremes

Lucas Butsch, Vicky Fasen-Hartmann

For multivariate regularly random vectors of dimension , the dependence structure of the extremes is modeled by the so-called angular measure. When the dimension is high, es…

stat.ME2024

Information criteria for the number of directions of extremes in high-dimensional data

Lucas Butsch, Vicky Fasen-Hartmann

In multivariate extreme value analysis, the estimation of the dependence structure in extremes is demanding, especially in the context of high-dimensional data. Therefore, a common…

math.ST2021

Factorization and discrete-time representation of multivariate CARMA processes

Vicky Fasen-Hartmann, Markus Scholz

In this paper we show that stationary and non-stationary multivariate continuous-time ARMA (MCARMA) processes have the representation as a sum of multivariate complex-valued Ornste…

math.ST2020

A note on estimation of -stable CARMA processes sampled at low frequencies

Vicky Fasen-Hartmann, Celeste Mayer

In this paper, we investigate estimators for symmetric -stable CARMA processes sampled equidistantly. Simulation studies suggest that the Whittle estimator and the estimator pre…

math.ST20202 cited

Whittle estimation for stationary state space models with finite second moments

Vicky Fasen-Hartmann, Celeste Mayer

In this paper, we consider the Whittle estimator for the parameters of a stationary solution of a continuous-time linear state space model sampled at low frequencies. In our contex…