12 citations · 23 across the 9 of their papers we have counts for
10 papers
Decomposing Global Bank Network Connectedness: What is Common, Idiosyncratic and When?
Jonas Krampe, Luca Margaritella
We propose a novel approach to estimate high-dimensional global bank network connectedness in both the time and frequency domains. By employing a factor model with sparse VAR idios…
Frequency Domain Statistical Inference for High-Dimensional Time Series
Jonas Krampe, Efstathios Paparoditis
Analyzing time series in the frequency domain enables the development of powerful tools for investigating the second-order characteristics of multivariate processes. Parameters lik…
Inverse covariance operators of multivariate nonstationary time series
Jonas Krampe, Suhasini Subba Rao
For multivariate stationary time series many important properties, such as partial correlation, graphical models and autoregressive representations are encoded in the inverse of it…
Factor Models with Sparse VAR Idiosyncratic Components
Jonas Krampe, Luca Margaritella
We reconcile the two worlds of dense and sparse modeling by exploiting the positive aspects of both. We employ a factor model and assume {the dynamic of the factors is non-pervasiv…
Estimation of the Distribution of the Individual Reproduction Number: The Case of the COVID-19 Pandemic
Alexander Braumann, Jonas Krampe, Jens-Peter Kreiss +1
We investigate the problem of estimating the distribution of the individual reproduction number governing the COVID-19 pandemic. Under the assumption that this random variable foll…
Structural Inference in Sparse High-Dimensional Vector Autoregressions
Jonas Krampe, Efstathios Paparoditis, Carsten Trenkler
We consider statistical inference for impulse responses in sparse, structural high-dimensional vector autoregressive (SVAR) systems. We introduce consistent estimators of impulse r…
Statistical Estimation of High-Dimensional Vector Autoregressive Models
Jonas Krampe, Efstathios Paparoditis
High-dimensional vector autoregressive (VAR) models are important tools for the analysis of multivariate time series. This paper focuses on high-dimensional time series and on the…
Time Series Modeling on Dynamic Networks
Jonas Krampe
This paper focuses on modeling the dynamic attributes of a dynamic network with a fixed number of vertices. These attributes are considered as time series which dependency structur…
Bootstrap Based Inference for Sparse High-Dimensional Time Series Models
J. Krampe, J-P. Kreiss, E. Paparoditis
Fitting sparse models to high-dimensional time series is an important area of statistical inference. In this paper we consider sparse vector autoregressive models and develop appro…
EstimatedWold Representation and Spectral Density-Driven Bootstrap for Time Series
Jonas Krampe, Jens-Peter Kreiss, Efstathios Paparoditis
The second-order dependence structure of purely nondeterministic stationary process is described by the coefficients of the famous Wold representation. These coefficients can be ob…