In this article, we propose a new approach for sequential monitoring of a general class of
parameters of a d-dimensional time series, which can be estimated by approximately linear …

We propose a new sequential monitoring scheme for changes in the parameters of a
multivariate time series. In contrast to procedures proposed in the literature which compare an …

This paper investigates the problem of detecting relevant change points in the mean vector,
say $\mu_{t}=(\mu_{t,1},\ldots ,\mu_{t,d})^{T}$ of a high dimensional time series $(Z_{t})_{t\in \…

Change point detection in high dimensional data has found considerable interest in recent
years. Most of the literature either designs methodology for a retrospective analysis, where …

Detecting change points in time series is an essential part of recent statistical research.
Change points, also called structural breaks, are points in time, at which the stochastic structure …

In the framework of materials design there is the demand for extensive databases of specific
materials properties. In this work we suggest an improved strategy for creating future …

We propose two new trading strategies which are based on a mathematical hypothesis testing
procedure identifying change points in the volatility structure of equity indices. In the first …

In this paper optimal designs for regression problems with spherical predictors of arbitrary
dimension are considered. Our work is motivated by applications in material sciences, where …

… Holger Dette, Josua Gösmann Ruhr-Universität Bochum Fakultät für Mathematik 44780
Bochum Germany …

In this paper we propose a new approach for sequential monitoring of a parameter of a d-dimensional
time series. We consider a closed-end-method, which is motivated by the …